Research ArticleA Novel Security Scheme Based on Instant EncryptedTransmission for Internet of Things
Chen Wang 1 Jian Shen 23 Qi Liu1 Yongjun Ren1 and Tong Li 4
1School of Computer and Software Nanjing University of Information Science amp Technology Nanjing 210044 China2Jiangsu Engineering Center of Network Monitoring Jiangsu Collaborative Innovation Center on Atmospheric Environment andEquipment Technology School of Computer and Software Nanjing University of Information Science amp TechnologyNanjing 210044 China3State Key Laboratory of Information Security Institute of Information Engineering China4College of Computer and Control Engineering Nankai University Tianjin 300071 China
Correspondence should be addressed to Tong Li litongziyimailnankaieducn
Received 29 March 2018 Accepted 15 April 2018 Published 17 May 2018
Academic Editor Laurence T Yang
Copyright copy 2018 Chen Wang et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited
Internet of Things (IoT) is a research field that has been continuously developed and innovated in recent years and is also animportant driving force for the improvement of peoplersquos life in the future There are lots of scenarios in IoT where we need tocollaborate through devices to complete tasks that is a device sends data to other devices and other devices operate on the aid ofthe data These transmitted data are often usersrsquo privacy data such as medical data and grid data We propose an instant encryptedtransmission based security scheme for such scenarios in IoT The analysis in this paper indicates that our scheme can guaranteethe security of usersrsquo data while ensuring rapid transmission and acquisition of instant IoT data
1 Introduction
The Internet of Things (IoT) is a novel network connectingitems such as users vehicles and home devices throughelectronic tags sensors actuators and interactive softwareIoT ensures the connection and communication between theobjects by digital means Scenarios such as intelligent vehiclesystem and smart home system can be more convenientcomprehensive and intelligent with the assistance of IoTtechnology [1 2]
IoT involves collaboration between different levels andvarious fields of technologies including hardware imageand video processing data mining remote control datasecurity and privacy protection [3ndash7] Experts and schol-ars have carried out many research achievements on IoTrelated technologies and their practical applications frommany aspects Note that IoT may involve usersrsquo sensitiveinformation such as behavior habits identity informationand medical data Therefore the data security protectionof IoT is particularly important Various security protocols
specially designed for IoT have been proposed to achievesecure communication ensure data integrity and secure datasharing in IoT However the research of efficient instantsecure transmission scheme is still in the exploratory stageInstant encrypted transmission is a technology that consumesfew resources and realizes information security in a shortperiod of time This kind of technology can be used in manyscenes especially in emergence situations such as accidentsfires To better illustrate this demand the situation when asmart home equipped with IoT is on fire is described in detail[8ndash14]
A smart home may be equipped with smoke detectionand analysis device temperature monitor image and videorecognition and analysis device gas valve control devicewindow control device and fire extinguishing device [15]Firstly it is necessary to find danger at the first time of thefire by means of smoke alarm temperature monitoring andvideo surveillance Secondly when the house is on fire thedevices need to collaborate to find out thematerial for the fireand the factors that may further spread the fire Finally the
HindawiSecurity and Communication NetworksVolume 2018 Article ID 3680851 7 pageshttpsdoiorg10115520183680851
2 Security and Communication Networks
Monitoring camera
Smoke detector
Window
Fire extinguishing device
Auxiliary
Figure 1 The illustration of IoT-auxiliary fire extinguishing
system can decide the state of windows and valves by judgingthe composition of fire objects and fire situation and controlthe fire by fire extinguishers and other actuators Figure 1 isan illustration of how a smart home equipped with IoT is onguard when the house firesMotivation of This Paper There are some special scenariosin IoT that require the implementation of instant encryptedtransmission between two entities The car accident in theintelligent vehicle system and the fire in the smart homesystem require rapid transmission of sensitive informationEspecially when there is a fire in a home the camera dataobtained from the home and the control instructions forvalves extinguishing devices and other actuators are veryimportant sensitive data The security scheme for transmit-ting these information is not only to ensure the security ofdata transmission but also to ensure the timeliness of dataTherefore it is particularly important to propose a novelsecurity scheme based on instant encrypted transmission forthe application of IoT in emergency
11 Our Contributions
(i) A special and practical application scenario is dis-cussed for now there are no research and discussionon IoT-based smart home fire emergency schemesAlthough this scenario rarely occurs it has importantresearch significance because it is likely to causepersonal safety and property damage In additionthe study of this scenario will be further extended tothe design of secure transmission schemes for similarscenarios such as car accidents
(ii) An instant encrypted transmission method is designedwe have tailored a method for IoT-based smarthome environments The method is mainly aimed
at early warning and rescue of fire in the smarthome networks At present few solutions have beenproposed for the transmission of private data underthis scenario
(iii) A security scheme that takes very little time is proposedthe scheme proposed in this paper can help to solvethe emergence response issue in the smart home envi-ronment It also can be applied to other scenarios thathave strict time requirements for the transmission ofencrypted data
12 Related Works Cloud computing technology [16ndash18] iscommonly utilized to solve various problems for IoT andalso brings many security challenges Many existing securityschemes can be applied into IoT with some improvements[19ndash23] Sajid et al [24] present the security challenges ofcloud-assisted IoT-based supervisory control and data acqui-sition systems and also provide the existing best practices andrecommendations for improving andmaintaining the systemsecurity
In addition IoT is one of the important technologies forsmart grid systems Chin et al [25] consider that energybig data needs to be stored thoughtfully and security andblackout warnings should be presented in the first time Sothey survey the security threats of energy big data in IoT-based smart grid systems
Besides most IoT devices require location services Loca-tion data often contains private information Chen et al[26] investigate robustness security and privacy issues inlocation-based services for IoT Cryptographic solutions forsecurity and privacy of location information and localizationand LBSs in IoT are listed and compared to each other in theirpaper
Saxena et al [27] present an authentication protocol forIoT-enabled LTE networkThey propose symmetric key algo-rithms for the efficiency They claim that the communicationoverhead of their protocol is also reduced
Aman et al [28] propose a physical unclonable functionbased lightweight mutual authentication protocol for IoTsystems The adaptability of this new technology in IoTremains to be further explored
Li et al [29] present a novel key encryption scheme toestablish a lightweight mutual authentication protocol forsmart city applications They claim that their protocol hasmade a trade-off between the efficiency and communicationcost without sacrificing the security
Sciancalepore et al [30] consider that the significantairtime consumption required to exchange multiple mes-sages and certificates and perform authentication and keyagreement which are the most important issues for IoT Sothey propose a public key authentication and key agreementscheme for IoT devices with minimal airtime consumption
Furthermore IoT is also an important industrial pillartechnology in the field of health care in the future Anovel authentication scheme for medicine anticounterfeitingsystems with IoT is presented by Wazid et al [31] Thenovel scheme is utilized for checking the authenticity ofpharmaceutical products
Security and Communication Networks 3
Parne et al [32] propose a novel AKA protocol basedon security enhanced group for M2M communication in aLTELTE-Anetwork utilizing IoT technologyThey claim thattheir novel protocol has better performance in overheads andfulfills security requirements of M2M communication
Although these solutions proposed and solved manyexisting IoT security problems none of them proposed asecure transmission scheme for IoT networks in a smarthome environment Simultaneously instant encrypted trans-missions in emergence situations have also not been consid-ered
13 Organization Theremainder of this paper is organized asfollows Section 2 presents some preliminaries of this paperSection 3 shows the security models of the novel schemeSection 4 presents the proposed scheme in detail Section 5states the security analysis of the proposed scheme Section 6presents the performance analysis of the scheme Finally theconclusions are drawn in Section 7
2 Preliminaries
In this section some necessary preliminaries utilized in thispaper are listed including bilinear pairing systemmodel andscheme components
21 Bilinear Pairing G1 andG2 are two groups of prime order119902 G1 is an additive group and G2 is a multiplicative groupSet 119890 as a mapping on (G1G2) G21 rarr G2 The cryptographicbilinear map 119890 satisfies the following propertiesBilinearity119890(119886119875 119887119876) = 119890(119875 119876)119886119887 for all 119875119876 isin G1 and119886 119887 isin 119885lowast119902 This can be expressed in the following mannerFor 119875119876 119877 isin G1 119890(119875 + 119876 119877) = 119890(119875 119877)119890(119876 119877)Nondegeneracy If 119875 is a generator of G1 then 119890(119875 119875) is agenerator of G2 In other words 119890(119875 119875) = 1Computability119890 is efficiently computable
22 System Model The system model of our novel scheme iscomposed of three roles KGC the sender and the receiverThe meanings of the three roles are introduced as follows
KGC KGC is an abbreviation of key generation center TheKGC is responsible for generating important parameters forregistering each node in the system including processingnode identity information generating system public andprivate keys and generating a unique identity-based privatekey for each node
Sender The sender can be a sensor such as an infrareddevice a temperature-sensitive device and a pressure-sensitive device or a detector such as a smoke detector Forinstance in a fire scenario the sender may need to collectvarious fire-related data in the room and encrypt the data fortransmission to other nodes
ReceiverThe receiver may be various types of actuators suchas fire extinguishing devices smart windows and gas valvesThe receiver needs to receive the fire-related information sentby the sender and decrypt the relevant information throughcertain calculations After real-time data is acquired corre-sponding operations are performed according to differentsituations
23 Scheme Components This subsection mainly introducesthe input and output parameters of the algorithms involvedin this scheme
Registration (ID 1119896)This phase is run by KGC The input ofthis phase is the ID number of the node The output is anID-related parameter 119902 a public key 119875pub and an ID-relatedprivate key 119904Detection (1199021 1199022 1199041 119898) The sender performs this phase Let1199021 1199022 the secret key 1199041 and the fire message 119898 be the inputThe output is encrypted message119872 certification message 119877and public key for this round119883Implementation(1199021 1199022 1199042119872 119877119883) This phase is run by thereceiver The receiver takes 1199021 1199022 his secret key 1199042 theencrypted message119872 the certification parameter 119877 and 119883as its input The output is the decrypted message119898
The above threemain algorithms constitute themain partof our new scheme
3 Security Model
In this section we introduce three security models for ourproposed scheme
31 A Forged Sender A forged sender may be a sensor nodein IoTwhose identity information has been stolenThe forgedsender can broadcast a wrong message using the identity ofthe real one This kind of wrong information can lead toextremely serious consequences For example when a houseis on fire an attacker can broadcast some normal monitoringdata which makes the whole system unable to monitor thefire for the first time In addition when a house is in a normalstate a forged node will send an ldquoon firerdquo signal to the wholesystem which will also cause irreparable damage to the user
32 Man-in-the-Middle (MITM) Attack A man-in-the-middle (MITM) attack refers to the situation that a man-in-the-middle intercepts the information sent by the sender andsends the information to the receiver after some malevolenttamperingThis can also cause the spread of false informationand serious consequences
33 An Unregistered Receiver An unregistered receiver mayhave access to private data about the userrsquos family such asimage and video data which will have a bad impact on theprivacy of the user Besides once the important timelinessinformation is received by the unregistered receiver it is likelyto affect the implementation of the IoT emergence measures
4 Security and Communication Networks
Sensor Detector
Key Generation Center (KGC)
Actuator
① Registration Phase
② Detection Phase ③ Implementation Phase
Figure 2 Overview of the proposed scheme
4 Our Proposed Scheme
In this section we elaborate on the novel scheme we haveproposed A simple overview of the proposed scheme ispresented On this basis we describe this scheme in threephases registration phase detection phase and implemen-tation phase
41 Overview of the Scheme The overview of the proposedscheme is presented in this subsection Figure 2 shows thevisualization of the new scheme in a concise form Thenovel scheme is composed of three phases which are namedregistration phase detection phase and implementationphase The registration phase is the initial phase of thescheme The key generation center (KGC) generates privatekeys of all sensorsdetectors and actuators in the networkaccording to their identity information Note that somenecessary offline calculations are completed at this phase toassist in subsequent phases We will elaborate on the contentof these calculations in the next subsection The detectionphase is actually a sign and encryption phase The subjectof the execution is named the sender in our model Thesender represents sensors such as temperature monitor anddetectors such as smoke detector and monitoring cameraThese devices are responsible for collecting editing andencrypting the transmission of detected fire informationThis phase requires the security of the collected data thatis related to privacy of the family and the message to besent out in a very short time The third phase is namedimplementation phase This phase is carried out by actuatorssuch as fire extinguishing devices smart windows and gasvalves This phase requires that the encrypted data is crackedand the identity authentication of the sender is completedin the very short time and the corresponding extinguishingoperation should be executed accordinglyThrough the abovethree phases the scheme we provide can accomplish thefast encrypted transmission of emergence information underthe IoT environment and accomplish the prevention andresponse to emergencies
42 Details of the Scheme Thedetails of the proposed schemeare shown in this subsection
421 Registration Phase The registration phasemainly refersto the process of each node in the network obtaining the
Sender Receiver
w = e(P P)xq1
M = m⨁H2(w)
x isinR Zlowast X = xP
R =q2s1X
s1 + x(M RX)
L =q1Ppub + X
s2
w = e(L R)
m = M⨁H2(w)
Figure 3 The detection and implementation phase of the scheme
necessary information from the KGC KGC first chooses asecret key 119905 for this system and calculates public key of thissystem 119875pub = 119905119875 Generate parameter 119902119898 related to node119898rsquos identity information by hash function1198671 119902119898 = 1198671(ID119898)The private key of the node 119898 is obtained by the calculationof the parameter 119902119898 and the private key 119905 and the private keyis written to the node memory 119904 = 119905119902119898422 Detection Phase The detection phase actually refers tothe process of monitoring the abnormal situation by sensorsor detectors and compiling these information into files andencrypting the transmission to other nodes The specificoperation process is illustrated in detail in Figure 3
The sender chooses a random number 119909 which is anonzero positive integer and calculates 119883 = 119909119875 Then thesender computes 119908
119908 = 119890 (119875 119875)1199091199021 (1)
where 119909 is the random number and 1199021 is the parametercalculated by KGC with the ID value of the sender
The sender compiles themonitored data into a file named119898 XOR operation is performed as follows
119872 = 119898 oplus1198672 (119908) (2)
The detection result 119872 which is the encrypted data isobtained according the above calculation
Security and Communication Networks 5
Finally a certification parameter 119877 is calculated119877 = 119902211990411198831199041 + 119909 (3)
where 1199022 is the parameter computed by KGC according tothe identity information of the receiver and 1199041 represents thesecret key of the sender which is generated by KGC
Finally the sender transmits the encrypted detectionresult119872 the certification parameter 119877 and the parameter119883to the receiver
423 Implementation Phase This phase refers to the processof the receiver accepting information and performing relatedemergence operationsThe receiver needs to first authenticatethe identity of the node sending the information
The receiver first computes a assistance parameter 119871119871 = 1199021119875pub + 1198831199042 (4)
where 1199021 is the parameter generated by KGC about theidentity information if the sender 119875pub is the public key ofsystem 119883 is the parameter sent by the sender and 1199042 is itsown private key
The parameter 1199081015840 is restored with the calculation 1199081015840 =119890(119871 119877) The message about the emergency is computed by119898 = 119872 oplus1198672(1199081015840)
Finally when obtaining the correct information thereceiver will implement related operations according to thereal-time information
5 Security Analysis
In this section the correctness of our scheme is firstly shownThen the security analysis is presented in aspects of securityagainst a forged sender MITM attack and an unregisteredreceiver
51 Correctness The correctness of a scheme is that thecalculation process of the design can eventually achieve thedesired goal and complete the expected security expectationFor the scheme we have designed correctness refers to thefact that the sender and the receiver can encrypt and decryptthe information through themethods we design respectively
We denote the new 119908 computed by the receiver as 1199081015840 1199081015840can be calculated as follows
Based on the above deduction it is not difficult to drawthe conclusion that the designed scheme is correct
52 Security against a Forged Sender An adversary maycompromise a sensor node or a detector node to send somefake alarmmessage Identity information of the sender mightbe stolen Such sender is called a forged sender
In our scheme the adversary can fake one 1205981 to replace 1199041but he knows nothing about 119905 So the adversary cannot matchhis fake 1205981 with 1199041 = 1199051198671(ID) Therefore a forged sendercannot send a 119877 that can be verified
53 Security against MITM Attack If an attacker wantsto capture or tamper with the content of the message byintercepting information he is called a man-in-the-middle
The attacker can intercept the message (119872 119877119883) of ourscheme If he wants to capture the specific message he needsto decrypt the message 119872 However he has no chance toknow about the parameter 119909 which is a random numbergenerated by the sender during every transmission It cannotbe excluded that he can break the message through thereceiver But in fact an attacker cannot know any recipientrsquosprivate key 1199042
In addition if the attacker wants to tamper with themessage he needs to generate a fake number 120575 to replacethe random number 119909 and regenerate 119877 Actually he knownothing about 1199041 so he cannot generate an effective 119877 If heeven forges 1199041 he will fall into the same embarrassment as theadversary in the previous subsection
Besides the attacker can constantly collect the encryptedmessage ciphertext and the original text sent before thesender However since 119909 is a random number which changesin every round he cannot infer the encrypted informationfrom the previous plaintext and ciphertext
54 Security against an Unregistered Receiver An unreg-istered receiver is an unlawful node but it can receiveencrypted information If the receiver is true and not reg-istered the sender will not be able to compute encryptedinformation that matches 1199022 Therefore it does not have thecorresponding 1199042 to decrypt the message
6 Performance Analysis
This section is going to discuss the performance of the pro-posed protocol The computational cost of different entitiesin the proposed scheme is shown in Table 1 We take intoconsideration the computational costs of the sender andthe receiver We consider the cost of collision-resistant hashfunction bilinear pairing scalar multiplication exclusive-OR and group exponent In Table 1 M represents scalarmultiplication P denotes bilinear pairing E refers to groupexponent H represents collision-resistant hash functionoperation and XOR denotes exclusive-OR By computationthe result comes out that a sender costs 2 scalar multiplica-tions 1 bilinear pairing 1 group exponent 1 collision-resistanthash function operations and 1 exclusive-OR for sendingthe message to one receiver In addition a receiver costs 1scalar multiplications 1 bilinear pairing 1 collision-resistanthash function operations and 1 exclusive-OR to rebuild themessage
Figure 4 The time cost of a sender when the number of receivergrows
5 10 15 20 25 30 35 40 45 500Number of Senders
0
100
200
300
400
500
600
Com
puta
tiona
l Cos
t of a
Rec
eive
r (m
s)
Figure 5 The time cost of a receiver when the number of sendergrows
The efficiency of the proposed scheme is simulated onGNU Multiple Precision Arithmetic (GMP) library andPairing-Based Cryptography (PBC) library (httpscryptostanfordedupbc) We utilize C language on a Linux systemwith Ubuntu 1604 TLS a 260GHz Intel(R) Xeon(R) CPUE5-2650 v2 and 8GB of RAM The results are illustrated inFigures 4 and 5 It is not difficult to see that both the senderrsquosand the receiverrsquos computational costs will increase as thenumber of the other party increases The increasing trend ofthe senderrsquos cost due to the increase in the number of theother party is slower Although our experiments simulate a
large number of nodes the number of nodes in a smart homenetwork is actually very limited Therefore we find that thenew scheme we propose costs very limited time to transmitemergence data Combining this scheme with efficient dataanalysis and instruction dispatching algorithms can achieveresponse to emergencies in a smart home environment
7 Conclusion
In this paper we propose a novel scheme based on instantencrypted transmission for IoT-based smart home systemThe three phases of the registration phase the detectionphase and the implementation phase constitute themain partof the overall scheme The simulation by PBC shows that ournovel scheme enables the transfer of important data in a veryshort period of time while protecting the privacy of data
Data Availability
The data used to support the findings of this study areavailable from the corresponding author upon request
Conflicts of Interest
The authors declare that they have no conflicts of interest
Acknowledgments
Thiswork is supported by theNational Natural Science Foun-dation of China under Grant no 61672295 no 61672290no U1405254 and no 61772280 the State Key Laboratory ofInformation Security under Grant no 2017-MS-10 the 2015Project of Six Personnel in Jiangsu Province under Grant noR2015L06 the CICAEET fund and the PAPD fund
References
[1] D Zhang L T Yang M Chen S Zhao M Guo and Y ZhangldquoReal-time locating systems using active rfid for internet ofthingsrdquo IEEE Systems Journal vol 10 no 3 pp 1226ndash1235 2016
[2] Z Zhou M Dong K Ota G Wang and L T Yang ldquoEnergy-efficient resource allocation for d2d communications under-laying cloud-ran-based lte-a networksrdquo IEEE Internet of ThingsJournal vol 3 no 3 pp 428ndash438 2016
[3] J Zhou Z Cao X Dong and A V Vasilakos ldquoSecurity andprivacy for cloud-based IoT challengesrdquo IEEE CommunicationsMagazine vol 55 no 1 pp 26ndash33 2017
[4] X Zhang Y Tan C Liang Y Li and J Li ldquoA covert channelover volte via adjusting silence periodsrdquo IEEE Access vol 6 pp9292ndash9302 2018
[5] J Shen T Zhou D He Y Zhang X Sun and Y XiangldquoBlock design-based key agreement for group data sharing in
Security and Communication Networks 7
cloud computingrdquo IEEE Transactions on Dependable and SecureComputing vol PP no 99 2017
[6] Q Lin J Li Z Huang W Chen and J Shen ldquoA short linearlyhomomorphic proxy signature schemerdquo IEEE Access vol 6 pp12966ndash12972 2018
[7] J Li J Li X Chen C Jia and W Lou ldquoIdentity-basedencryption with outsourced revocation in cloud computingrdquoInstitute of Electrical and Electronics Engineers Transactions onComputers vol 64 no 2 pp 425ndash437 2015
[8] Y Xiang W Zhou and M Guo ldquoFlexible deterministic packetmarking An IP traceback system to find the real source ofattacksrdquo IEEE Transactions on Parallel and Distributed Systemsvol 20 no 4 pp 567ndash580 2009
[9] J Shen T Zhou X Chen J Li and W Susilo ldquoAnonymousand traceable group data sharing in cloud computingrdquo IEEETransactions on Information Forensics and Security vol 13 no4 pp 912ndash925 2018
[10] X Chen J Li X Huang J Ma and W Lou ldquoNew PubliclyVerifiable Databases with Efficient Updatesrdquo IEEE Transactionson Dependable and Secure Computing vol 12 no 5 pp 546ndash556 2015
[11] Q Lin H Yan Z Huang W Chen J Shen and Y TangldquoAn ID-based linearly homomorphic signature scheme and itsapplication in blockchainrdquo IEEE Access vol 6 2018
[12] M Z Alam Bhuiyan J Wu G Wang and J Cao ldquoSensingand decision making in cyber-physical systems the case ofstructural event monitoringrdquo IEEE Transactions on IndustrialInformatics vol 12 no 6 pp 2103ndash2114 2016
[13] H Liu H Ning Y Zhang Q Xiong and L T Yang ldquoRole-dependent privacy preservation for secure v2 g networks inthe smart gridrdquo IEEE Transactions on Information Forensics ampSecurity vol 9 no 2 pp 208ndash220 2017
[14] J Li Y K Li X Chen P P C Lee and W Lou ldquoA hybridcloud approach for secure authorized deduplicationrdquo Parallelamp Distributed Systems IEEE Transactions on vol 26 no 5 pp1206ndash1216 2015
[15] J Shen C Wang C-F Lai A Wang and H-C Chao ldquoDirec-tion Density-Based Secure Routing Protocol for HealthcareData in Incompletely Predictable Networksrdquo IEEE Access vol4 pp 9163ndash9173 2016
[16] Y Yu M H Au G Ateniese et al ldquoIdentity-Based RemoteData Integrity Checking with Perfect Data Privacy Preservingfor Cloud Storagerdquo IEEE Transactions on Information Forensicsand Security vol 12 no 4 pp 767ndash778 2017
[17] J Shen J Shen X Chen X Huang and W Susilo ldquoAn efficientpublic auditing protocol with novel dynamic structure for clouddatardquo IEEE Transactions on Information Forensics and Securityvol 12 no 10 pp 2402ndash2415 2017
[18] P Li J Li Z Huang et al ldquoMulti-key privacy-preserving deeplearning in cloud computingrdquo Future Generation ComputerSystems vol 74 pp 76ndash85 2017
[19] T Jiang X Chen and JMa ldquoPublic integrity auditing for shareddynamic cloud data with group user revocationrdquo Institute ofElectrical and Electronics Engineers Transactions on Computersvol 65 no 8 pp 2363ndash2373 2016
[20] X Chen J Li J Weng J Ma andW Lou ldquoVerifiable computa-tion over large database with incremental updatesrdquo Institute ofElectrical and Electronics Engineers Transactions on Computersvol 65 no 10 pp 3184ndash3195 2016
[21] J Li Y Zhang X Chen and Y Xiang ldquoSecure attribute-baseddata sharing for resource-limited users in cloud computingrdquoComputersSecurity vol 72 p 12 2018
[22] J Shen D Liu J Shen Q Liu and X Sun ldquoA secure cloud-assisted urban data sharing framework for ubiquitous-citiesrdquoPervasive and Mobile Computing 2017
[23] J Yu and H Wang ldquoStrong key-exposure resilient auditingfor secure cloud storagerdquo IEEE Transactions on InformationForensics and Security vol 12 no 8 pp 1931ndash1940 2017
[24] A Sajid H Abbas and K Saleem ldquoCloud-Assisted IoT-BasedSCADA Systems Security A Review of the State of the Art andFuture Challengesrdquo IEEE Access vol 4 pp 1375ndash1384 2016
[25] W-L Chin W Li and H-H Chen ldquoEnergy Big Data SecurityThreats in IoT-Based Smart Grid Communicationsrdquo IEEECommunications Magazine vol 55 no 10 pp 70ndash75 2017
[26] L Chen S Thombre K Jarvinen et al et al ldquoRobustnesssecurity and privacy in location-based services for future iota surveyrdquo IEEE Access vol 5 pp 8956ndash8977 2017
[27] N Saxena S Grijalva and N S Chaudhari ldquoAuthenticationprotocol for an iot-enabled LTE networkrdquoACMTransactions onInternet Technology (TOIT) vol 16 no 4 article no 25 2016
[28] M N Aman K C Chua and B Sikdar ldquoA light-weight mutualauthentication protocol for iot systemsrdquo in Proceedings of theGLOBECOM IEEE Global Communications Conference pp 1ndash6 2017
[29] N Li D Liu and S Nepal ldquoLightweight mutual authenticationfor iot and its applicationsrdquo IEEE Transactions on SustainableComputing vol 2 no 4 pp 359ndash370 2017
[30] S Sciancalepore G Piro G Boggia andG Bianchi ldquoPublic keyauthentication and key agreement in iot devices with minimalairtime consumptionrdquo IEEE Embedded Systems Letters vol 9no 1 pp 1ndash4 2017
[31] M Wazid A K Das M K Khan A A-D Al-Ghaiheb NKumar and A V Vasilakos ldquoSecure authentication scheme formedicine anti-counterfeiting system in iot environmentrdquo IEEEInternet of Things Journal vol 4 no 5 pp 1634ndash1646 2017
[32] B L Parne S Gupta and N S Chaudhari ldquoSegb Securityenhanced group based aka protocol form2mcommunication inan iot enabled ltelte-a networkrdquo IEEE Access vol 6 pp 3668ndash3684 2018
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawiwwwhindawicom Volume 2018
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Navigation and Observation
International Journal of
Hindawi
wwwhindawicom Volume 2018
Advances in
Multimedia
Submit your manuscripts atwwwhindawicom
2 Security and Communication Networks
Monitoring camera
Smoke detector
Window
Fire extinguishing device
Auxiliary
Figure 1 The illustration of IoT-auxiliary fire extinguishing
system can decide the state of windows and valves by judgingthe composition of fire objects and fire situation and controlthe fire by fire extinguishers and other actuators Figure 1 isan illustration of how a smart home equipped with IoT is onguard when the house firesMotivation of This Paper There are some special scenariosin IoT that require the implementation of instant encryptedtransmission between two entities The car accident in theintelligent vehicle system and the fire in the smart homesystem require rapid transmission of sensitive informationEspecially when there is a fire in a home the camera dataobtained from the home and the control instructions forvalves extinguishing devices and other actuators are veryimportant sensitive data The security scheme for transmit-ting these information is not only to ensure the security ofdata transmission but also to ensure the timeliness of dataTherefore it is particularly important to propose a novelsecurity scheme based on instant encrypted transmission forthe application of IoT in emergency
11 Our Contributions
(i) A special and practical application scenario is dis-cussed for now there are no research and discussionon IoT-based smart home fire emergency schemesAlthough this scenario rarely occurs it has importantresearch significance because it is likely to causepersonal safety and property damage In additionthe study of this scenario will be further extended tothe design of secure transmission schemes for similarscenarios such as car accidents
(ii) An instant encrypted transmission method is designedwe have tailored a method for IoT-based smarthome environments The method is mainly aimed
at early warning and rescue of fire in the smarthome networks At present few solutions have beenproposed for the transmission of private data underthis scenario
(iii) A security scheme that takes very little time is proposedthe scheme proposed in this paper can help to solvethe emergence response issue in the smart home envi-ronment It also can be applied to other scenarios thathave strict time requirements for the transmission ofencrypted data
12 Related Works Cloud computing technology [16ndash18] iscommonly utilized to solve various problems for IoT andalso brings many security challenges Many existing securityschemes can be applied into IoT with some improvements[19ndash23] Sajid et al [24] present the security challenges ofcloud-assisted IoT-based supervisory control and data acqui-sition systems and also provide the existing best practices andrecommendations for improving andmaintaining the systemsecurity
In addition IoT is one of the important technologies forsmart grid systems Chin et al [25] consider that energybig data needs to be stored thoughtfully and security andblackout warnings should be presented in the first time Sothey survey the security threats of energy big data in IoT-based smart grid systems
Besides most IoT devices require location services Loca-tion data often contains private information Chen et al[26] investigate robustness security and privacy issues inlocation-based services for IoT Cryptographic solutions forsecurity and privacy of location information and localizationand LBSs in IoT are listed and compared to each other in theirpaper
Saxena et al [27] present an authentication protocol forIoT-enabled LTE networkThey propose symmetric key algo-rithms for the efficiency They claim that the communicationoverhead of their protocol is also reduced
Aman et al [28] propose a physical unclonable functionbased lightweight mutual authentication protocol for IoTsystems The adaptability of this new technology in IoTremains to be further explored
Li et al [29] present a novel key encryption scheme toestablish a lightweight mutual authentication protocol forsmart city applications They claim that their protocol hasmade a trade-off between the efficiency and communicationcost without sacrificing the security
Sciancalepore et al [30] consider that the significantairtime consumption required to exchange multiple mes-sages and certificates and perform authentication and keyagreement which are the most important issues for IoT Sothey propose a public key authentication and key agreementscheme for IoT devices with minimal airtime consumption
Furthermore IoT is also an important industrial pillartechnology in the field of health care in the future Anovel authentication scheme for medicine anticounterfeitingsystems with IoT is presented by Wazid et al [31] Thenovel scheme is utilized for checking the authenticity ofpharmaceutical products
Security and Communication Networks 3
Parne et al [32] propose a novel AKA protocol basedon security enhanced group for M2M communication in aLTELTE-Anetwork utilizing IoT technologyThey claim thattheir novel protocol has better performance in overheads andfulfills security requirements of M2M communication
Although these solutions proposed and solved manyexisting IoT security problems none of them proposed asecure transmission scheme for IoT networks in a smarthome environment Simultaneously instant encrypted trans-missions in emergence situations have also not been consid-ered
13 Organization Theremainder of this paper is organized asfollows Section 2 presents some preliminaries of this paperSection 3 shows the security models of the novel schemeSection 4 presents the proposed scheme in detail Section 5states the security analysis of the proposed scheme Section 6presents the performance analysis of the scheme Finally theconclusions are drawn in Section 7
2 Preliminaries
In this section some necessary preliminaries utilized in thispaper are listed including bilinear pairing systemmodel andscheme components
21 Bilinear Pairing G1 andG2 are two groups of prime order119902 G1 is an additive group and G2 is a multiplicative groupSet 119890 as a mapping on (G1G2) G21 rarr G2 The cryptographicbilinear map 119890 satisfies the following propertiesBilinearity119890(119886119875 119887119876) = 119890(119875 119876)119886119887 for all 119875119876 isin G1 and119886 119887 isin 119885lowast119902 This can be expressed in the following mannerFor 119875119876 119877 isin G1 119890(119875 + 119876 119877) = 119890(119875 119877)119890(119876 119877)Nondegeneracy If 119875 is a generator of G1 then 119890(119875 119875) is agenerator of G2 In other words 119890(119875 119875) = 1Computability119890 is efficiently computable
22 System Model The system model of our novel scheme iscomposed of three roles KGC the sender and the receiverThe meanings of the three roles are introduced as follows
KGC KGC is an abbreviation of key generation center TheKGC is responsible for generating important parameters forregistering each node in the system including processingnode identity information generating system public andprivate keys and generating a unique identity-based privatekey for each node
Sender The sender can be a sensor such as an infrareddevice a temperature-sensitive device and a pressure-sensitive device or a detector such as a smoke detector Forinstance in a fire scenario the sender may need to collectvarious fire-related data in the room and encrypt the data fortransmission to other nodes
ReceiverThe receiver may be various types of actuators suchas fire extinguishing devices smart windows and gas valvesThe receiver needs to receive the fire-related information sentby the sender and decrypt the relevant information throughcertain calculations After real-time data is acquired corre-sponding operations are performed according to differentsituations
23 Scheme Components This subsection mainly introducesthe input and output parameters of the algorithms involvedin this scheme
Registration (ID 1119896)This phase is run by KGC The input ofthis phase is the ID number of the node The output is anID-related parameter 119902 a public key 119875pub and an ID-relatedprivate key 119904Detection (1199021 1199022 1199041 119898) The sender performs this phase Let1199021 1199022 the secret key 1199041 and the fire message 119898 be the inputThe output is encrypted message119872 certification message 119877and public key for this round119883Implementation(1199021 1199022 1199042119872 119877119883) This phase is run by thereceiver The receiver takes 1199021 1199022 his secret key 1199042 theencrypted message119872 the certification parameter 119877 and 119883as its input The output is the decrypted message119898
The above threemain algorithms constitute themain partof our new scheme
3 Security Model
In this section we introduce three security models for ourproposed scheme
31 A Forged Sender A forged sender may be a sensor nodein IoTwhose identity information has been stolenThe forgedsender can broadcast a wrong message using the identity ofthe real one This kind of wrong information can lead toextremely serious consequences For example when a houseis on fire an attacker can broadcast some normal monitoringdata which makes the whole system unable to monitor thefire for the first time In addition when a house is in a normalstate a forged node will send an ldquoon firerdquo signal to the wholesystem which will also cause irreparable damage to the user
32 Man-in-the-Middle (MITM) Attack A man-in-the-middle (MITM) attack refers to the situation that a man-in-the-middle intercepts the information sent by the sender andsends the information to the receiver after some malevolenttamperingThis can also cause the spread of false informationand serious consequences
33 An Unregistered Receiver An unregistered receiver mayhave access to private data about the userrsquos family such asimage and video data which will have a bad impact on theprivacy of the user Besides once the important timelinessinformation is received by the unregistered receiver it is likelyto affect the implementation of the IoT emergence measures
4 Security and Communication Networks
Sensor Detector
Key Generation Center (KGC)
Actuator
① Registration Phase
② Detection Phase ③ Implementation Phase
Figure 2 Overview of the proposed scheme
4 Our Proposed Scheme
In this section we elaborate on the novel scheme we haveproposed A simple overview of the proposed scheme ispresented On this basis we describe this scheme in threephases registration phase detection phase and implemen-tation phase
41 Overview of the Scheme The overview of the proposedscheme is presented in this subsection Figure 2 shows thevisualization of the new scheme in a concise form Thenovel scheme is composed of three phases which are namedregistration phase detection phase and implementationphase The registration phase is the initial phase of thescheme The key generation center (KGC) generates privatekeys of all sensorsdetectors and actuators in the networkaccording to their identity information Note that somenecessary offline calculations are completed at this phase toassist in subsequent phases We will elaborate on the contentof these calculations in the next subsection The detectionphase is actually a sign and encryption phase The subjectof the execution is named the sender in our model Thesender represents sensors such as temperature monitor anddetectors such as smoke detector and monitoring cameraThese devices are responsible for collecting editing andencrypting the transmission of detected fire informationThis phase requires the security of the collected data thatis related to privacy of the family and the message to besent out in a very short time The third phase is namedimplementation phase This phase is carried out by actuatorssuch as fire extinguishing devices smart windows and gasvalves This phase requires that the encrypted data is crackedand the identity authentication of the sender is completedin the very short time and the corresponding extinguishingoperation should be executed accordinglyThrough the abovethree phases the scheme we provide can accomplish thefast encrypted transmission of emergence information underthe IoT environment and accomplish the prevention andresponse to emergencies
42 Details of the Scheme Thedetails of the proposed schemeare shown in this subsection
421 Registration Phase The registration phasemainly refersto the process of each node in the network obtaining the
Sender Receiver
w = e(P P)xq1
M = m⨁H2(w)
x isinR Zlowast X = xP
R =q2s1X
s1 + x(M RX)
L =q1Ppub + X
s2
w = e(L R)
m = M⨁H2(w)
Figure 3 The detection and implementation phase of the scheme
necessary information from the KGC KGC first chooses asecret key 119905 for this system and calculates public key of thissystem 119875pub = 119905119875 Generate parameter 119902119898 related to node119898rsquos identity information by hash function1198671 119902119898 = 1198671(ID119898)The private key of the node 119898 is obtained by the calculationof the parameter 119902119898 and the private key 119905 and the private keyis written to the node memory 119904 = 119905119902119898422 Detection Phase The detection phase actually refers tothe process of monitoring the abnormal situation by sensorsor detectors and compiling these information into files andencrypting the transmission to other nodes The specificoperation process is illustrated in detail in Figure 3
The sender chooses a random number 119909 which is anonzero positive integer and calculates 119883 = 119909119875 Then thesender computes 119908
119908 = 119890 (119875 119875)1199091199021 (1)
where 119909 is the random number and 1199021 is the parametercalculated by KGC with the ID value of the sender
The sender compiles themonitored data into a file named119898 XOR operation is performed as follows
119872 = 119898 oplus1198672 (119908) (2)
The detection result 119872 which is the encrypted data isobtained according the above calculation
Security and Communication Networks 5
Finally a certification parameter 119877 is calculated119877 = 119902211990411198831199041 + 119909 (3)
where 1199022 is the parameter computed by KGC according tothe identity information of the receiver and 1199041 represents thesecret key of the sender which is generated by KGC
Finally the sender transmits the encrypted detectionresult119872 the certification parameter 119877 and the parameter119883to the receiver
423 Implementation Phase This phase refers to the processof the receiver accepting information and performing relatedemergence operationsThe receiver needs to first authenticatethe identity of the node sending the information
The receiver first computes a assistance parameter 119871119871 = 1199021119875pub + 1198831199042 (4)
where 1199021 is the parameter generated by KGC about theidentity information if the sender 119875pub is the public key ofsystem 119883 is the parameter sent by the sender and 1199042 is itsown private key
The parameter 1199081015840 is restored with the calculation 1199081015840 =119890(119871 119877) The message about the emergency is computed by119898 = 119872 oplus1198672(1199081015840)
Finally when obtaining the correct information thereceiver will implement related operations according to thereal-time information
5 Security Analysis
In this section the correctness of our scheme is firstly shownThen the security analysis is presented in aspects of securityagainst a forged sender MITM attack and an unregisteredreceiver
51 Correctness The correctness of a scheme is that thecalculation process of the design can eventually achieve thedesired goal and complete the expected security expectationFor the scheme we have designed correctness refers to thefact that the sender and the receiver can encrypt and decryptthe information through themethods we design respectively
We denote the new 119908 computed by the receiver as 1199081015840 1199081015840can be calculated as follows
Based on the above deduction it is not difficult to drawthe conclusion that the designed scheme is correct
52 Security against a Forged Sender An adversary maycompromise a sensor node or a detector node to send somefake alarmmessage Identity information of the sender mightbe stolen Such sender is called a forged sender
In our scheme the adversary can fake one 1205981 to replace 1199041but he knows nothing about 119905 So the adversary cannot matchhis fake 1205981 with 1199041 = 1199051198671(ID) Therefore a forged sendercannot send a 119877 that can be verified
53 Security against MITM Attack If an attacker wantsto capture or tamper with the content of the message byintercepting information he is called a man-in-the-middle
The attacker can intercept the message (119872 119877119883) of ourscheme If he wants to capture the specific message he needsto decrypt the message 119872 However he has no chance toknow about the parameter 119909 which is a random numbergenerated by the sender during every transmission It cannotbe excluded that he can break the message through thereceiver But in fact an attacker cannot know any recipientrsquosprivate key 1199042
In addition if the attacker wants to tamper with themessage he needs to generate a fake number 120575 to replacethe random number 119909 and regenerate 119877 Actually he knownothing about 1199041 so he cannot generate an effective 119877 If heeven forges 1199041 he will fall into the same embarrassment as theadversary in the previous subsection
Besides the attacker can constantly collect the encryptedmessage ciphertext and the original text sent before thesender However since 119909 is a random number which changesin every round he cannot infer the encrypted informationfrom the previous plaintext and ciphertext
54 Security against an Unregistered Receiver An unreg-istered receiver is an unlawful node but it can receiveencrypted information If the receiver is true and not reg-istered the sender will not be able to compute encryptedinformation that matches 1199022 Therefore it does not have thecorresponding 1199042 to decrypt the message
6 Performance Analysis
This section is going to discuss the performance of the pro-posed protocol The computational cost of different entitiesin the proposed scheme is shown in Table 1 We take intoconsideration the computational costs of the sender andthe receiver We consider the cost of collision-resistant hashfunction bilinear pairing scalar multiplication exclusive-OR and group exponent In Table 1 M represents scalarmultiplication P denotes bilinear pairing E refers to groupexponent H represents collision-resistant hash functionoperation and XOR denotes exclusive-OR By computationthe result comes out that a sender costs 2 scalar multiplica-tions 1 bilinear pairing 1 group exponent 1 collision-resistanthash function operations and 1 exclusive-OR for sendingthe message to one receiver In addition a receiver costs 1scalar multiplications 1 bilinear pairing 1 collision-resistanthash function operations and 1 exclusive-OR to rebuild themessage
Figure 4 The time cost of a sender when the number of receivergrows
5 10 15 20 25 30 35 40 45 500Number of Senders
0
100
200
300
400
500
600
Com
puta
tiona
l Cos
t of a
Rec
eive
r (m
s)
Figure 5 The time cost of a receiver when the number of sendergrows
The efficiency of the proposed scheme is simulated onGNU Multiple Precision Arithmetic (GMP) library andPairing-Based Cryptography (PBC) library (httpscryptostanfordedupbc) We utilize C language on a Linux systemwith Ubuntu 1604 TLS a 260GHz Intel(R) Xeon(R) CPUE5-2650 v2 and 8GB of RAM The results are illustrated inFigures 4 and 5 It is not difficult to see that both the senderrsquosand the receiverrsquos computational costs will increase as thenumber of the other party increases The increasing trend ofthe senderrsquos cost due to the increase in the number of theother party is slower Although our experiments simulate a
large number of nodes the number of nodes in a smart homenetwork is actually very limited Therefore we find that thenew scheme we propose costs very limited time to transmitemergence data Combining this scheme with efficient dataanalysis and instruction dispatching algorithms can achieveresponse to emergencies in a smart home environment
7 Conclusion
In this paper we propose a novel scheme based on instantencrypted transmission for IoT-based smart home systemThe three phases of the registration phase the detectionphase and the implementation phase constitute themain partof the overall scheme The simulation by PBC shows that ournovel scheme enables the transfer of important data in a veryshort period of time while protecting the privacy of data
Data Availability
The data used to support the findings of this study areavailable from the corresponding author upon request
Conflicts of Interest
The authors declare that they have no conflicts of interest
Acknowledgments
Thiswork is supported by theNational Natural Science Foun-dation of China under Grant no 61672295 no 61672290no U1405254 and no 61772280 the State Key Laboratory ofInformation Security under Grant no 2017-MS-10 the 2015Project of Six Personnel in Jiangsu Province under Grant noR2015L06 the CICAEET fund and the PAPD fund
References
[1] D Zhang L T Yang M Chen S Zhao M Guo and Y ZhangldquoReal-time locating systems using active rfid for internet ofthingsrdquo IEEE Systems Journal vol 10 no 3 pp 1226ndash1235 2016
[2] Z Zhou M Dong K Ota G Wang and L T Yang ldquoEnergy-efficient resource allocation for d2d communications under-laying cloud-ran-based lte-a networksrdquo IEEE Internet of ThingsJournal vol 3 no 3 pp 428ndash438 2016
[3] J Zhou Z Cao X Dong and A V Vasilakos ldquoSecurity andprivacy for cloud-based IoT challengesrdquo IEEE CommunicationsMagazine vol 55 no 1 pp 26ndash33 2017
[4] X Zhang Y Tan C Liang Y Li and J Li ldquoA covert channelover volte via adjusting silence periodsrdquo IEEE Access vol 6 pp9292ndash9302 2018
[5] J Shen T Zhou D He Y Zhang X Sun and Y XiangldquoBlock design-based key agreement for group data sharing in
Security and Communication Networks 7
cloud computingrdquo IEEE Transactions on Dependable and SecureComputing vol PP no 99 2017
[6] Q Lin J Li Z Huang W Chen and J Shen ldquoA short linearlyhomomorphic proxy signature schemerdquo IEEE Access vol 6 pp12966ndash12972 2018
[7] J Li J Li X Chen C Jia and W Lou ldquoIdentity-basedencryption with outsourced revocation in cloud computingrdquoInstitute of Electrical and Electronics Engineers Transactions onComputers vol 64 no 2 pp 425ndash437 2015
[8] Y Xiang W Zhou and M Guo ldquoFlexible deterministic packetmarking An IP traceback system to find the real source ofattacksrdquo IEEE Transactions on Parallel and Distributed Systemsvol 20 no 4 pp 567ndash580 2009
[9] J Shen T Zhou X Chen J Li and W Susilo ldquoAnonymousand traceable group data sharing in cloud computingrdquo IEEETransactions on Information Forensics and Security vol 13 no4 pp 912ndash925 2018
[10] X Chen J Li X Huang J Ma and W Lou ldquoNew PubliclyVerifiable Databases with Efficient Updatesrdquo IEEE Transactionson Dependable and Secure Computing vol 12 no 5 pp 546ndash556 2015
[11] Q Lin H Yan Z Huang W Chen J Shen and Y TangldquoAn ID-based linearly homomorphic signature scheme and itsapplication in blockchainrdquo IEEE Access vol 6 2018
[12] M Z Alam Bhuiyan J Wu G Wang and J Cao ldquoSensingand decision making in cyber-physical systems the case ofstructural event monitoringrdquo IEEE Transactions on IndustrialInformatics vol 12 no 6 pp 2103ndash2114 2016
[13] H Liu H Ning Y Zhang Q Xiong and L T Yang ldquoRole-dependent privacy preservation for secure v2 g networks inthe smart gridrdquo IEEE Transactions on Information Forensics ampSecurity vol 9 no 2 pp 208ndash220 2017
[14] J Li Y K Li X Chen P P C Lee and W Lou ldquoA hybridcloud approach for secure authorized deduplicationrdquo Parallelamp Distributed Systems IEEE Transactions on vol 26 no 5 pp1206ndash1216 2015
[15] J Shen C Wang C-F Lai A Wang and H-C Chao ldquoDirec-tion Density-Based Secure Routing Protocol for HealthcareData in Incompletely Predictable Networksrdquo IEEE Access vol4 pp 9163ndash9173 2016
[16] Y Yu M H Au G Ateniese et al ldquoIdentity-Based RemoteData Integrity Checking with Perfect Data Privacy Preservingfor Cloud Storagerdquo IEEE Transactions on Information Forensicsand Security vol 12 no 4 pp 767ndash778 2017
[17] J Shen J Shen X Chen X Huang and W Susilo ldquoAn efficientpublic auditing protocol with novel dynamic structure for clouddatardquo IEEE Transactions on Information Forensics and Securityvol 12 no 10 pp 2402ndash2415 2017
[18] P Li J Li Z Huang et al ldquoMulti-key privacy-preserving deeplearning in cloud computingrdquo Future Generation ComputerSystems vol 74 pp 76ndash85 2017
[19] T Jiang X Chen and JMa ldquoPublic integrity auditing for shareddynamic cloud data with group user revocationrdquo Institute ofElectrical and Electronics Engineers Transactions on Computersvol 65 no 8 pp 2363ndash2373 2016
[20] X Chen J Li J Weng J Ma andW Lou ldquoVerifiable computa-tion over large database with incremental updatesrdquo Institute ofElectrical and Electronics Engineers Transactions on Computersvol 65 no 10 pp 3184ndash3195 2016
[21] J Li Y Zhang X Chen and Y Xiang ldquoSecure attribute-baseddata sharing for resource-limited users in cloud computingrdquoComputersSecurity vol 72 p 12 2018
[22] J Shen D Liu J Shen Q Liu and X Sun ldquoA secure cloud-assisted urban data sharing framework for ubiquitous-citiesrdquoPervasive and Mobile Computing 2017
[23] J Yu and H Wang ldquoStrong key-exposure resilient auditingfor secure cloud storagerdquo IEEE Transactions on InformationForensics and Security vol 12 no 8 pp 1931ndash1940 2017
[24] A Sajid H Abbas and K Saleem ldquoCloud-Assisted IoT-BasedSCADA Systems Security A Review of the State of the Art andFuture Challengesrdquo IEEE Access vol 4 pp 1375ndash1384 2016
[25] W-L Chin W Li and H-H Chen ldquoEnergy Big Data SecurityThreats in IoT-Based Smart Grid Communicationsrdquo IEEECommunications Magazine vol 55 no 10 pp 70ndash75 2017
[26] L Chen S Thombre K Jarvinen et al et al ldquoRobustnesssecurity and privacy in location-based services for future iota surveyrdquo IEEE Access vol 5 pp 8956ndash8977 2017
[27] N Saxena S Grijalva and N S Chaudhari ldquoAuthenticationprotocol for an iot-enabled LTE networkrdquoACMTransactions onInternet Technology (TOIT) vol 16 no 4 article no 25 2016
[28] M N Aman K C Chua and B Sikdar ldquoA light-weight mutualauthentication protocol for iot systemsrdquo in Proceedings of theGLOBECOM IEEE Global Communications Conference pp 1ndash6 2017
[29] N Li D Liu and S Nepal ldquoLightweight mutual authenticationfor iot and its applicationsrdquo IEEE Transactions on SustainableComputing vol 2 no 4 pp 359ndash370 2017
[30] S Sciancalepore G Piro G Boggia andG Bianchi ldquoPublic keyauthentication and key agreement in iot devices with minimalairtime consumptionrdquo IEEE Embedded Systems Letters vol 9no 1 pp 1ndash4 2017
[31] M Wazid A K Das M K Khan A A-D Al-Ghaiheb NKumar and A V Vasilakos ldquoSecure authentication scheme formedicine anti-counterfeiting system in iot environmentrdquo IEEEInternet of Things Journal vol 4 no 5 pp 1634ndash1646 2017
[32] B L Parne S Gupta and N S Chaudhari ldquoSegb Securityenhanced group based aka protocol form2mcommunication inan iot enabled ltelte-a networkrdquo IEEE Access vol 6 pp 3668ndash3684 2018
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawiwwwhindawicom Volume 2018
Hindawiwwwhindawicom Volume 2018
Navigation and Observation
International Journal of
Hindawi
wwwhindawicom Volume 2018
Advances in
Multimedia
Submit your manuscripts atwwwhindawicom
Security and Communication Networks 3
Parne et al [32] propose a novel AKA protocol basedon security enhanced group for M2M communication in aLTELTE-Anetwork utilizing IoT technologyThey claim thattheir novel protocol has better performance in overheads andfulfills security requirements of M2M communication
Although these solutions proposed and solved manyexisting IoT security problems none of them proposed asecure transmission scheme for IoT networks in a smarthome environment Simultaneously instant encrypted trans-missions in emergence situations have also not been consid-ered
13 Organization Theremainder of this paper is organized asfollows Section 2 presents some preliminaries of this paperSection 3 shows the security models of the novel schemeSection 4 presents the proposed scheme in detail Section 5states the security analysis of the proposed scheme Section 6presents the performance analysis of the scheme Finally theconclusions are drawn in Section 7
2 Preliminaries
In this section some necessary preliminaries utilized in thispaper are listed including bilinear pairing systemmodel andscheme components
21 Bilinear Pairing G1 andG2 are two groups of prime order119902 G1 is an additive group and G2 is a multiplicative groupSet 119890 as a mapping on (G1G2) G21 rarr G2 The cryptographicbilinear map 119890 satisfies the following propertiesBilinearity119890(119886119875 119887119876) = 119890(119875 119876)119886119887 for all 119875119876 isin G1 and119886 119887 isin 119885lowast119902 This can be expressed in the following mannerFor 119875119876 119877 isin G1 119890(119875 + 119876 119877) = 119890(119875 119877)119890(119876 119877)Nondegeneracy If 119875 is a generator of G1 then 119890(119875 119875) is agenerator of G2 In other words 119890(119875 119875) = 1Computability119890 is efficiently computable
22 System Model The system model of our novel scheme iscomposed of three roles KGC the sender and the receiverThe meanings of the three roles are introduced as follows
KGC KGC is an abbreviation of key generation center TheKGC is responsible for generating important parameters forregistering each node in the system including processingnode identity information generating system public andprivate keys and generating a unique identity-based privatekey for each node
Sender The sender can be a sensor such as an infrareddevice a temperature-sensitive device and a pressure-sensitive device or a detector such as a smoke detector Forinstance in a fire scenario the sender may need to collectvarious fire-related data in the room and encrypt the data fortransmission to other nodes
ReceiverThe receiver may be various types of actuators suchas fire extinguishing devices smart windows and gas valvesThe receiver needs to receive the fire-related information sentby the sender and decrypt the relevant information throughcertain calculations After real-time data is acquired corre-sponding operations are performed according to differentsituations
23 Scheme Components This subsection mainly introducesthe input and output parameters of the algorithms involvedin this scheme
Registration (ID 1119896)This phase is run by KGC The input ofthis phase is the ID number of the node The output is anID-related parameter 119902 a public key 119875pub and an ID-relatedprivate key 119904Detection (1199021 1199022 1199041 119898) The sender performs this phase Let1199021 1199022 the secret key 1199041 and the fire message 119898 be the inputThe output is encrypted message119872 certification message 119877and public key for this round119883Implementation(1199021 1199022 1199042119872 119877119883) This phase is run by thereceiver The receiver takes 1199021 1199022 his secret key 1199042 theencrypted message119872 the certification parameter 119877 and 119883as its input The output is the decrypted message119898
The above threemain algorithms constitute themain partof our new scheme
3 Security Model
In this section we introduce three security models for ourproposed scheme
31 A Forged Sender A forged sender may be a sensor nodein IoTwhose identity information has been stolenThe forgedsender can broadcast a wrong message using the identity ofthe real one This kind of wrong information can lead toextremely serious consequences For example when a houseis on fire an attacker can broadcast some normal monitoringdata which makes the whole system unable to monitor thefire for the first time In addition when a house is in a normalstate a forged node will send an ldquoon firerdquo signal to the wholesystem which will also cause irreparable damage to the user
32 Man-in-the-Middle (MITM) Attack A man-in-the-middle (MITM) attack refers to the situation that a man-in-the-middle intercepts the information sent by the sender andsends the information to the receiver after some malevolenttamperingThis can also cause the spread of false informationand serious consequences
33 An Unregistered Receiver An unregistered receiver mayhave access to private data about the userrsquos family such asimage and video data which will have a bad impact on theprivacy of the user Besides once the important timelinessinformation is received by the unregistered receiver it is likelyto affect the implementation of the IoT emergence measures
4 Security and Communication Networks
Sensor Detector
Key Generation Center (KGC)
Actuator
① Registration Phase
② Detection Phase ③ Implementation Phase
Figure 2 Overview of the proposed scheme
4 Our Proposed Scheme
In this section we elaborate on the novel scheme we haveproposed A simple overview of the proposed scheme ispresented On this basis we describe this scheme in threephases registration phase detection phase and implemen-tation phase
41 Overview of the Scheme The overview of the proposedscheme is presented in this subsection Figure 2 shows thevisualization of the new scheme in a concise form Thenovel scheme is composed of three phases which are namedregistration phase detection phase and implementationphase The registration phase is the initial phase of thescheme The key generation center (KGC) generates privatekeys of all sensorsdetectors and actuators in the networkaccording to their identity information Note that somenecessary offline calculations are completed at this phase toassist in subsequent phases We will elaborate on the contentof these calculations in the next subsection The detectionphase is actually a sign and encryption phase The subjectof the execution is named the sender in our model Thesender represents sensors such as temperature monitor anddetectors such as smoke detector and monitoring cameraThese devices are responsible for collecting editing andencrypting the transmission of detected fire informationThis phase requires the security of the collected data thatis related to privacy of the family and the message to besent out in a very short time The third phase is namedimplementation phase This phase is carried out by actuatorssuch as fire extinguishing devices smart windows and gasvalves This phase requires that the encrypted data is crackedand the identity authentication of the sender is completedin the very short time and the corresponding extinguishingoperation should be executed accordinglyThrough the abovethree phases the scheme we provide can accomplish thefast encrypted transmission of emergence information underthe IoT environment and accomplish the prevention andresponse to emergencies
42 Details of the Scheme Thedetails of the proposed schemeare shown in this subsection
421 Registration Phase The registration phasemainly refersto the process of each node in the network obtaining the
Sender Receiver
w = e(P P)xq1
M = m⨁H2(w)
x isinR Zlowast X = xP
R =q2s1X
s1 + x(M RX)
L =q1Ppub + X
s2
w = e(L R)
m = M⨁H2(w)
Figure 3 The detection and implementation phase of the scheme
necessary information from the KGC KGC first chooses asecret key 119905 for this system and calculates public key of thissystem 119875pub = 119905119875 Generate parameter 119902119898 related to node119898rsquos identity information by hash function1198671 119902119898 = 1198671(ID119898)The private key of the node 119898 is obtained by the calculationof the parameter 119902119898 and the private key 119905 and the private keyis written to the node memory 119904 = 119905119902119898422 Detection Phase The detection phase actually refers tothe process of monitoring the abnormal situation by sensorsor detectors and compiling these information into files andencrypting the transmission to other nodes The specificoperation process is illustrated in detail in Figure 3
The sender chooses a random number 119909 which is anonzero positive integer and calculates 119883 = 119909119875 Then thesender computes 119908
119908 = 119890 (119875 119875)1199091199021 (1)
where 119909 is the random number and 1199021 is the parametercalculated by KGC with the ID value of the sender
The sender compiles themonitored data into a file named119898 XOR operation is performed as follows
119872 = 119898 oplus1198672 (119908) (2)
The detection result 119872 which is the encrypted data isobtained according the above calculation
Security and Communication Networks 5
Finally a certification parameter 119877 is calculated119877 = 119902211990411198831199041 + 119909 (3)
where 1199022 is the parameter computed by KGC according tothe identity information of the receiver and 1199041 represents thesecret key of the sender which is generated by KGC
Finally the sender transmits the encrypted detectionresult119872 the certification parameter 119877 and the parameter119883to the receiver
423 Implementation Phase This phase refers to the processof the receiver accepting information and performing relatedemergence operationsThe receiver needs to first authenticatethe identity of the node sending the information
The receiver first computes a assistance parameter 119871119871 = 1199021119875pub + 1198831199042 (4)
where 1199021 is the parameter generated by KGC about theidentity information if the sender 119875pub is the public key ofsystem 119883 is the parameter sent by the sender and 1199042 is itsown private key
The parameter 1199081015840 is restored with the calculation 1199081015840 =119890(119871 119877) The message about the emergency is computed by119898 = 119872 oplus1198672(1199081015840)
Finally when obtaining the correct information thereceiver will implement related operations according to thereal-time information
5 Security Analysis
In this section the correctness of our scheme is firstly shownThen the security analysis is presented in aspects of securityagainst a forged sender MITM attack and an unregisteredreceiver
51 Correctness The correctness of a scheme is that thecalculation process of the design can eventually achieve thedesired goal and complete the expected security expectationFor the scheme we have designed correctness refers to thefact that the sender and the receiver can encrypt and decryptthe information through themethods we design respectively
We denote the new 119908 computed by the receiver as 1199081015840 1199081015840can be calculated as follows
Based on the above deduction it is not difficult to drawthe conclusion that the designed scheme is correct
52 Security against a Forged Sender An adversary maycompromise a sensor node or a detector node to send somefake alarmmessage Identity information of the sender mightbe stolen Such sender is called a forged sender
In our scheme the adversary can fake one 1205981 to replace 1199041but he knows nothing about 119905 So the adversary cannot matchhis fake 1205981 with 1199041 = 1199051198671(ID) Therefore a forged sendercannot send a 119877 that can be verified
53 Security against MITM Attack If an attacker wantsto capture or tamper with the content of the message byintercepting information he is called a man-in-the-middle
The attacker can intercept the message (119872 119877119883) of ourscheme If he wants to capture the specific message he needsto decrypt the message 119872 However he has no chance toknow about the parameter 119909 which is a random numbergenerated by the sender during every transmission It cannotbe excluded that he can break the message through thereceiver But in fact an attacker cannot know any recipientrsquosprivate key 1199042
In addition if the attacker wants to tamper with themessage he needs to generate a fake number 120575 to replacethe random number 119909 and regenerate 119877 Actually he knownothing about 1199041 so he cannot generate an effective 119877 If heeven forges 1199041 he will fall into the same embarrassment as theadversary in the previous subsection
Besides the attacker can constantly collect the encryptedmessage ciphertext and the original text sent before thesender However since 119909 is a random number which changesin every round he cannot infer the encrypted informationfrom the previous plaintext and ciphertext
54 Security against an Unregistered Receiver An unreg-istered receiver is an unlawful node but it can receiveencrypted information If the receiver is true and not reg-istered the sender will not be able to compute encryptedinformation that matches 1199022 Therefore it does not have thecorresponding 1199042 to decrypt the message
6 Performance Analysis
This section is going to discuss the performance of the pro-posed protocol The computational cost of different entitiesin the proposed scheme is shown in Table 1 We take intoconsideration the computational costs of the sender andthe receiver We consider the cost of collision-resistant hashfunction bilinear pairing scalar multiplication exclusive-OR and group exponent In Table 1 M represents scalarmultiplication P denotes bilinear pairing E refers to groupexponent H represents collision-resistant hash functionoperation and XOR denotes exclusive-OR By computationthe result comes out that a sender costs 2 scalar multiplica-tions 1 bilinear pairing 1 group exponent 1 collision-resistanthash function operations and 1 exclusive-OR for sendingthe message to one receiver In addition a receiver costs 1scalar multiplications 1 bilinear pairing 1 collision-resistanthash function operations and 1 exclusive-OR to rebuild themessage
Figure 4 The time cost of a sender when the number of receivergrows
5 10 15 20 25 30 35 40 45 500Number of Senders
0
100
200
300
400
500
600
Com
puta
tiona
l Cos
t of a
Rec
eive
r (m
s)
Figure 5 The time cost of a receiver when the number of sendergrows
The efficiency of the proposed scheme is simulated onGNU Multiple Precision Arithmetic (GMP) library andPairing-Based Cryptography (PBC) library (httpscryptostanfordedupbc) We utilize C language on a Linux systemwith Ubuntu 1604 TLS a 260GHz Intel(R) Xeon(R) CPUE5-2650 v2 and 8GB of RAM The results are illustrated inFigures 4 and 5 It is not difficult to see that both the senderrsquosand the receiverrsquos computational costs will increase as thenumber of the other party increases The increasing trend ofthe senderrsquos cost due to the increase in the number of theother party is slower Although our experiments simulate a
large number of nodes the number of nodes in a smart homenetwork is actually very limited Therefore we find that thenew scheme we propose costs very limited time to transmitemergence data Combining this scheme with efficient dataanalysis and instruction dispatching algorithms can achieveresponse to emergencies in a smart home environment
7 Conclusion
In this paper we propose a novel scheme based on instantencrypted transmission for IoT-based smart home systemThe three phases of the registration phase the detectionphase and the implementation phase constitute themain partof the overall scheme The simulation by PBC shows that ournovel scheme enables the transfer of important data in a veryshort period of time while protecting the privacy of data
Data Availability
The data used to support the findings of this study areavailable from the corresponding author upon request
Conflicts of Interest
The authors declare that they have no conflicts of interest
Acknowledgments
Thiswork is supported by theNational Natural Science Foun-dation of China under Grant no 61672295 no 61672290no U1405254 and no 61772280 the State Key Laboratory ofInformation Security under Grant no 2017-MS-10 the 2015Project of Six Personnel in Jiangsu Province under Grant noR2015L06 the CICAEET fund and the PAPD fund
References
[1] D Zhang L T Yang M Chen S Zhao M Guo and Y ZhangldquoReal-time locating systems using active rfid for internet ofthingsrdquo IEEE Systems Journal vol 10 no 3 pp 1226ndash1235 2016
[2] Z Zhou M Dong K Ota G Wang and L T Yang ldquoEnergy-efficient resource allocation for d2d communications under-laying cloud-ran-based lte-a networksrdquo IEEE Internet of ThingsJournal vol 3 no 3 pp 428ndash438 2016
[3] J Zhou Z Cao X Dong and A V Vasilakos ldquoSecurity andprivacy for cloud-based IoT challengesrdquo IEEE CommunicationsMagazine vol 55 no 1 pp 26ndash33 2017
[4] X Zhang Y Tan C Liang Y Li and J Li ldquoA covert channelover volte via adjusting silence periodsrdquo IEEE Access vol 6 pp9292ndash9302 2018
[5] J Shen T Zhou D He Y Zhang X Sun and Y XiangldquoBlock design-based key agreement for group data sharing in
Security and Communication Networks 7
cloud computingrdquo IEEE Transactions on Dependable and SecureComputing vol PP no 99 2017
[6] Q Lin J Li Z Huang W Chen and J Shen ldquoA short linearlyhomomorphic proxy signature schemerdquo IEEE Access vol 6 pp12966ndash12972 2018
[7] J Li J Li X Chen C Jia and W Lou ldquoIdentity-basedencryption with outsourced revocation in cloud computingrdquoInstitute of Electrical and Electronics Engineers Transactions onComputers vol 64 no 2 pp 425ndash437 2015
[8] Y Xiang W Zhou and M Guo ldquoFlexible deterministic packetmarking An IP traceback system to find the real source ofattacksrdquo IEEE Transactions on Parallel and Distributed Systemsvol 20 no 4 pp 567ndash580 2009
[9] J Shen T Zhou X Chen J Li and W Susilo ldquoAnonymousand traceable group data sharing in cloud computingrdquo IEEETransactions on Information Forensics and Security vol 13 no4 pp 912ndash925 2018
[10] X Chen J Li X Huang J Ma and W Lou ldquoNew PubliclyVerifiable Databases with Efficient Updatesrdquo IEEE Transactionson Dependable and Secure Computing vol 12 no 5 pp 546ndash556 2015
[11] Q Lin H Yan Z Huang W Chen J Shen and Y TangldquoAn ID-based linearly homomorphic signature scheme and itsapplication in blockchainrdquo IEEE Access vol 6 2018
[12] M Z Alam Bhuiyan J Wu G Wang and J Cao ldquoSensingand decision making in cyber-physical systems the case ofstructural event monitoringrdquo IEEE Transactions on IndustrialInformatics vol 12 no 6 pp 2103ndash2114 2016
[13] H Liu H Ning Y Zhang Q Xiong and L T Yang ldquoRole-dependent privacy preservation for secure v2 g networks inthe smart gridrdquo IEEE Transactions on Information Forensics ampSecurity vol 9 no 2 pp 208ndash220 2017
[14] J Li Y K Li X Chen P P C Lee and W Lou ldquoA hybridcloud approach for secure authorized deduplicationrdquo Parallelamp Distributed Systems IEEE Transactions on vol 26 no 5 pp1206ndash1216 2015
[15] J Shen C Wang C-F Lai A Wang and H-C Chao ldquoDirec-tion Density-Based Secure Routing Protocol for HealthcareData in Incompletely Predictable Networksrdquo IEEE Access vol4 pp 9163ndash9173 2016
[16] Y Yu M H Au G Ateniese et al ldquoIdentity-Based RemoteData Integrity Checking with Perfect Data Privacy Preservingfor Cloud Storagerdquo IEEE Transactions on Information Forensicsand Security vol 12 no 4 pp 767ndash778 2017
[17] J Shen J Shen X Chen X Huang and W Susilo ldquoAn efficientpublic auditing protocol with novel dynamic structure for clouddatardquo IEEE Transactions on Information Forensics and Securityvol 12 no 10 pp 2402ndash2415 2017
[18] P Li J Li Z Huang et al ldquoMulti-key privacy-preserving deeplearning in cloud computingrdquo Future Generation ComputerSystems vol 74 pp 76ndash85 2017
[19] T Jiang X Chen and JMa ldquoPublic integrity auditing for shareddynamic cloud data with group user revocationrdquo Institute ofElectrical and Electronics Engineers Transactions on Computersvol 65 no 8 pp 2363ndash2373 2016
[20] X Chen J Li J Weng J Ma andW Lou ldquoVerifiable computa-tion over large database with incremental updatesrdquo Institute ofElectrical and Electronics Engineers Transactions on Computersvol 65 no 10 pp 3184ndash3195 2016
[21] J Li Y Zhang X Chen and Y Xiang ldquoSecure attribute-baseddata sharing for resource-limited users in cloud computingrdquoComputersSecurity vol 72 p 12 2018
[22] J Shen D Liu J Shen Q Liu and X Sun ldquoA secure cloud-assisted urban data sharing framework for ubiquitous-citiesrdquoPervasive and Mobile Computing 2017
[23] J Yu and H Wang ldquoStrong key-exposure resilient auditingfor secure cloud storagerdquo IEEE Transactions on InformationForensics and Security vol 12 no 8 pp 1931ndash1940 2017
[24] A Sajid H Abbas and K Saleem ldquoCloud-Assisted IoT-BasedSCADA Systems Security A Review of the State of the Art andFuture Challengesrdquo IEEE Access vol 4 pp 1375ndash1384 2016
[25] W-L Chin W Li and H-H Chen ldquoEnergy Big Data SecurityThreats in IoT-Based Smart Grid Communicationsrdquo IEEECommunications Magazine vol 55 no 10 pp 70ndash75 2017
[26] L Chen S Thombre K Jarvinen et al et al ldquoRobustnesssecurity and privacy in location-based services for future iota surveyrdquo IEEE Access vol 5 pp 8956ndash8977 2017
[27] N Saxena S Grijalva and N S Chaudhari ldquoAuthenticationprotocol for an iot-enabled LTE networkrdquoACMTransactions onInternet Technology (TOIT) vol 16 no 4 article no 25 2016
[28] M N Aman K C Chua and B Sikdar ldquoA light-weight mutualauthentication protocol for iot systemsrdquo in Proceedings of theGLOBECOM IEEE Global Communications Conference pp 1ndash6 2017
[29] N Li D Liu and S Nepal ldquoLightweight mutual authenticationfor iot and its applicationsrdquo IEEE Transactions on SustainableComputing vol 2 no 4 pp 359ndash370 2017
[30] S Sciancalepore G Piro G Boggia andG Bianchi ldquoPublic keyauthentication and key agreement in iot devices with minimalairtime consumptionrdquo IEEE Embedded Systems Letters vol 9no 1 pp 1ndash4 2017
[31] M Wazid A K Das M K Khan A A-D Al-Ghaiheb NKumar and A V Vasilakos ldquoSecure authentication scheme formedicine anti-counterfeiting system in iot environmentrdquo IEEEInternet of Things Journal vol 4 no 5 pp 1634ndash1646 2017
[32] B L Parne S Gupta and N S Chaudhari ldquoSegb Securityenhanced group based aka protocol form2mcommunication inan iot enabled ltelte-a networkrdquo IEEE Access vol 6 pp 3668ndash3684 2018
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawiwwwhindawicom Volume 2018
Hindawiwwwhindawicom Volume 2018
Navigation and Observation
International Journal of
Hindawi
wwwhindawicom Volume 2018
Advances in
Multimedia
Submit your manuscripts atwwwhindawicom
4 Security and Communication Networks
Sensor Detector
Key Generation Center (KGC)
Actuator
① Registration Phase
② Detection Phase ③ Implementation Phase
Figure 2 Overview of the proposed scheme
4 Our Proposed Scheme
In this section we elaborate on the novel scheme we haveproposed A simple overview of the proposed scheme ispresented On this basis we describe this scheme in threephases registration phase detection phase and implemen-tation phase
41 Overview of the Scheme The overview of the proposedscheme is presented in this subsection Figure 2 shows thevisualization of the new scheme in a concise form Thenovel scheme is composed of three phases which are namedregistration phase detection phase and implementationphase The registration phase is the initial phase of thescheme The key generation center (KGC) generates privatekeys of all sensorsdetectors and actuators in the networkaccording to their identity information Note that somenecessary offline calculations are completed at this phase toassist in subsequent phases We will elaborate on the contentof these calculations in the next subsection The detectionphase is actually a sign and encryption phase The subjectof the execution is named the sender in our model Thesender represents sensors such as temperature monitor anddetectors such as smoke detector and monitoring cameraThese devices are responsible for collecting editing andencrypting the transmission of detected fire informationThis phase requires the security of the collected data thatis related to privacy of the family and the message to besent out in a very short time The third phase is namedimplementation phase This phase is carried out by actuatorssuch as fire extinguishing devices smart windows and gasvalves This phase requires that the encrypted data is crackedand the identity authentication of the sender is completedin the very short time and the corresponding extinguishingoperation should be executed accordinglyThrough the abovethree phases the scheme we provide can accomplish thefast encrypted transmission of emergence information underthe IoT environment and accomplish the prevention andresponse to emergencies
42 Details of the Scheme Thedetails of the proposed schemeare shown in this subsection
421 Registration Phase The registration phasemainly refersto the process of each node in the network obtaining the
Sender Receiver
w = e(P P)xq1
M = m⨁H2(w)
x isinR Zlowast X = xP
R =q2s1X
s1 + x(M RX)
L =q1Ppub + X
s2
w = e(L R)
m = M⨁H2(w)
Figure 3 The detection and implementation phase of the scheme
necessary information from the KGC KGC first chooses asecret key 119905 for this system and calculates public key of thissystem 119875pub = 119905119875 Generate parameter 119902119898 related to node119898rsquos identity information by hash function1198671 119902119898 = 1198671(ID119898)The private key of the node 119898 is obtained by the calculationof the parameter 119902119898 and the private key 119905 and the private keyis written to the node memory 119904 = 119905119902119898422 Detection Phase The detection phase actually refers tothe process of monitoring the abnormal situation by sensorsor detectors and compiling these information into files andencrypting the transmission to other nodes The specificoperation process is illustrated in detail in Figure 3
The sender chooses a random number 119909 which is anonzero positive integer and calculates 119883 = 119909119875 Then thesender computes 119908
119908 = 119890 (119875 119875)1199091199021 (1)
where 119909 is the random number and 1199021 is the parametercalculated by KGC with the ID value of the sender
The sender compiles themonitored data into a file named119898 XOR operation is performed as follows
119872 = 119898 oplus1198672 (119908) (2)
The detection result 119872 which is the encrypted data isobtained according the above calculation
Security and Communication Networks 5
Finally a certification parameter 119877 is calculated119877 = 119902211990411198831199041 + 119909 (3)
where 1199022 is the parameter computed by KGC according tothe identity information of the receiver and 1199041 represents thesecret key of the sender which is generated by KGC
Finally the sender transmits the encrypted detectionresult119872 the certification parameter 119877 and the parameter119883to the receiver
423 Implementation Phase This phase refers to the processof the receiver accepting information and performing relatedemergence operationsThe receiver needs to first authenticatethe identity of the node sending the information
The receiver first computes a assistance parameter 119871119871 = 1199021119875pub + 1198831199042 (4)
where 1199021 is the parameter generated by KGC about theidentity information if the sender 119875pub is the public key ofsystem 119883 is the parameter sent by the sender and 1199042 is itsown private key
The parameter 1199081015840 is restored with the calculation 1199081015840 =119890(119871 119877) The message about the emergency is computed by119898 = 119872 oplus1198672(1199081015840)
Finally when obtaining the correct information thereceiver will implement related operations according to thereal-time information
5 Security Analysis
In this section the correctness of our scheme is firstly shownThen the security analysis is presented in aspects of securityagainst a forged sender MITM attack and an unregisteredreceiver
51 Correctness The correctness of a scheme is that thecalculation process of the design can eventually achieve thedesired goal and complete the expected security expectationFor the scheme we have designed correctness refers to thefact that the sender and the receiver can encrypt and decryptthe information through themethods we design respectively
We denote the new 119908 computed by the receiver as 1199081015840 1199081015840can be calculated as follows
Based on the above deduction it is not difficult to drawthe conclusion that the designed scheme is correct
52 Security against a Forged Sender An adversary maycompromise a sensor node or a detector node to send somefake alarmmessage Identity information of the sender mightbe stolen Such sender is called a forged sender
In our scheme the adversary can fake one 1205981 to replace 1199041but he knows nothing about 119905 So the adversary cannot matchhis fake 1205981 with 1199041 = 1199051198671(ID) Therefore a forged sendercannot send a 119877 that can be verified
53 Security against MITM Attack If an attacker wantsto capture or tamper with the content of the message byintercepting information he is called a man-in-the-middle
The attacker can intercept the message (119872 119877119883) of ourscheme If he wants to capture the specific message he needsto decrypt the message 119872 However he has no chance toknow about the parameter 119909 which is a random numbergenerated by the sender during every transmission It cannotbe excluded that he can break the message through thereceiver But in fact an attacker cannot know any recipientrsquosprivate key 1199042
In addition if the attacker wants to tamper with themessage he needs to generate a fake number 120575 to replacethe random number 119909 and regenerate 119877 Actually he knownothing about 1199041 so he cannot generate an effective 119877 If heeven forges 1199041 he will fall into the same embarrassment as theadversary in the previous subsection
Besides the attacker can constantly collect the encryptedmessage ciphertext and the original text sent before thesender However since 119909 is a random number which changesin every round he cannot infer the encrypted informationfrom the previous plaintext and ciphertext
54 Security against an Unregistered Receiver An unreg-istered receiver is an unlawful node but it can receiveencrypted information If the receiver is true and not reg-istered the sender will not be able to compute encryptedinformation that matches 1199022 Therefore it does not have thecorresponding 1199042 to decrypt the message
6 Performance Analysis
This section is going to discuss the performance of the pro-posed protocol The computational cost of different entitiesin the proposed scheme is shown in Table 1 We take intoconsideration the computational costs of the sender andthe receiver We consider the cost of collision-resistant hashfunction bilinear pairing scalar multiplication exclusive-OR and group exponent In Table 1 M represents scalarmultiplication P denotes bilinear pairing E refers to groupexponent H represents collision-resistant hash functionoperation and XOR denotes exclusive-OR By computationthe result comes out that a sender costs 2 scalar multiplica-tions 1 bilinear pairing 1 group exponent 1 collision-resistanthash function operations and 1 exclusive-OR for sendingthe message to one receiver In addition a receiver costs 1scalar multiplications 1 bilinear pairing 1 collision-resistanthash function operations and 1 exclusive-OR to rebuild themessage
Figure 4 The time cost of a sender when the number of receivergrows
5 10 15 20 25 30 35 40 45 500Number of Senders
0
100
200
300
400
500
600
Com
puta
tiona
l Cos
t of a
Rec
eive
r (m
s)
Figure 5 The time cost of a receiver when the number of sendergrows
The efficiency of the proposed scheme is simulated onGNU Multiple Precision Arithmetic (GMP) library andPairing-Based Cryptography (PBC) library (httpscryptostanfordedupbc) We utilize C language on a Linux systemwith Ubuntu 1604 TLS a 260GHz Intel(R) Xeon(R) CPUE5-2650 v2 and 8GB of RAM The results are illustrated inFigures 4 and 5 It is not difficult to see that both the senderrsquosand the receiverrsquos computational costs will increase as thenumber of the other party increases The increasing trend ofthe senderrsquos cost due to the increase in the number of theother party is slower Although our experiments simulate a
large number of nodes the number of nodes in a smart homenetwork is actually very limited Therefore we find that thenew scheme we propose costs very limited time to transmitemergence data Combining this scheme with efficient dataanalysis and instruction dispatching algorithms can achieveresponse to emergencies in a smart home environment
7 Conclusion
In this paper we propose a novel scheme based on instantencrypted transmission for IoT-based smart home systemThe three phases of the registration phase the detectionphase and the implementation phase constitute themain partof the overall scheme The simulation by PBC shows that ournovel scheme enables the transfer of important data in a veryshort period of time while protecting the privacy of data
Data Availability
The data used to support the findings of this study areavailable from the corresponding author upon request
Conflicts of Interest
The authors declare that they have no conflicts of interest
Acknowledgments
Thiswork is supported by theNational Natural Science Foun-dation of China under Grant no 61672295 no 61672290no U1405254 and no 61772280 the State Key Laboratory ofInformation Security under Grant no 2017-MS-10 the 2015Project of Six Personnel in Jiangsu Province under Grant noR2015L06 the CICAEET fund and the PAPD fund
References
[1] D Zhang L T Yang M Chen S Zhao M Guo and Y ZhangldquoReal-time locating systems using active rfid for internet ofthingsrdquo IEEE Systems Journal vol 10 no 3 pp 1226ndash1235 2016
[2] Z Zhou M Dong K Ota G Wang and L T Yang ldquoEnergy-efficient resource allocation for d2d communications under-laying cloud-ran-based lte-a networksrdquo IEEE Internet of ThingsJournal vol 3 no 3 pp 428ndash438 2016
[3] J Zhou Z Cao X Dong and A V Vasilakos ldquoSecurity andprivacy for cloud-based IoT challengesrdquo IEEE CommunicationsMagazine vol 55 no 1 pp 26ndash33 2017
[4] X Zhang Y Tan C Liang Y Li and J Li ldquoA covert channelover volte via adjusting silence periodsrdquo IEEE Access vol 6 pp9292ndash9302 2018
[5] J Shen T Zhou D He Y Zhang X Sun and Y XiangldquoBlock design-based key agreement for group data sharing in
Security and Communication Networks 7
cloud computingrdquo IEEE Transactions on Dependable and SecureComputing vol PP no 99 2017
[6] Q Lin J Li Z Huang W Chen and J Shen ldquoA short linearlyhomomorphic proxy signature schemerdquo IEEE Access vol 6 pp12966ndash12972 2018
[7] J Li J Li X Chen C Jia and W Lou ldquoIdentity-basedencryption with outsourced revocation in cloud computingrdquoInstitute of Electrical and Electronics Engineers Transactions onComputers vol 64 no 2 pp 425ndash437 2015
[8] Y Xiang W Zhou and M Guo ldquoFlexible deterministic packetmarking An IP traceback system to find the real source ofattacksrdquo IEEE Transactions on Parallel and Distributed Systemsvol 20 no 4 pp 567ndash580 2009
[9] J Shen T Zhou X Chen J Li and W Susilo ldquoAnonymousand traceable group data sharing in cloud computingrdquo IEEETransactions on Information Forensics and Security vol 13 no4 pp 912ndash925 2018
[10] X Chen J Li X Huang J Ma and W Lou ldquoNew PubliclyVerifiable Databases with Efficient Updatesrdquo IEEE Transactionson Dependable and Secure Computing vol 12 no 5 pp 546ndash556 2015
[11] Q Lin H Yan Z Huang W Chen J Shen and Y TangldquoAn ID-based linearly homomorphic signature scheme and itsapplication in blockchainrdquo IEEE Access vol 6 2018
[12] M Z Alam Bhuiyan J Wu G Wang and J Cao ldquoSensingand decision making in cyber-physical systems the case ofstructural event monitoringrdquo IEEE Transactions on IndustrialInformatics vol 12 no 6 pp 2103ndash2114 2016
[13] H Liu H Ning Y Zhang Q Xiong and L T Yang ldquoRole-dependent privacy preservation for secure v2 g networks inthe smart gridrdquo IEEE Transactions on Information Forensics ampSecurity vol 9 no 2 pp 208ndash220 2017
[14] J Li Y K Li X Chen P P C Lee and W Lou ldquoA hybridcloud approach for secure authorized deduplicationrdquo Parallelamp Distributed Systems IEEE Transactions on vol 26 no 5 pp1206ndash1216 2015
[15] J Shen C Wang C-F Lai A Wang and H-C Chao ldquoDirec-tion Density-Based Secure Routing Protocol for HealthcareData in Incompletely Predictable Networksrdquo IEEE Access vol4 pp 9163ndash9173 2016
[16] Y Yu M H Au G Ateniese et al ldquoIdentity-Based RemoteData Integrity Checking with Perfect Data Privacy Preservingfor Cloud Storagerdquo IEEE Transactions on Information Forensicsand Security vol 12 no 4 pp 767ndash778 2017
[17] J Shen J Shen X Chen X Huang and W Susilo ldquoAn efficientpublic auditing protocol with novel dynamic structure for clouddatardquo IEEE Transactions on Information Forensics and Securityvol 12 no 10 pp 2402ndash2415 2017
[18] P Li J Li Z Huang et al ldquoMulti-key privacy-preserving deeplearning in cloud computingrdquo Future Generation ComputerSystems vol 74 pp 76ndash85 2017
[19] T Jiang X Chen and JMa ldquoPublic integrity auditing for shareddynamic cloud data with group user revocationrdquo Institute ofElectrical and Electronics Engineers Transactions on Computersvol 65 no 8 pp 2363ndash2373 2016
[20] X Chen J Li J Weng J Ma andW Lou ldquoVerifiable computa-tion over large database with incremental updatesrdquo Institute ofElectrical and Electronics Engineers Transactions on Computersvol 65 no 10 pp 3184ndash3195 2016
[21] J Li Y Zhang X Chen and Y Xiang ldquoSecure attribute-baseddata sharing for resource-limited users in cloud computingrdquoComputersSecurity vol 72 p 12 2018
[22] J Shen D Liu J Shen Q Liu and X Sun ldquoA secure cloud-assisted urban data sharing framework for ubiquitous-citiesrdquoPervasive and Mobile Computing 2017
[23] J Yu and H Wang ldquoStrong key-exposure resilient auditingfor secure cloud storagerdquo IEEE Transactions on InformationForensics and Security vol 12 no 8 pp 1931ndash1940 2017
[24] A Sajid H Abbas and K Saleem ldquoCloud-Assisted IoT-BasedSCADA Systems Security A Review of the State of the Art andFuture Challengesrdquo IEEE Access vol 4 pp 1375ndash1384 2016
[25] W-L Chin W Li and H-H Chen ldquoEnergy Big Data SecurityThreats in IoT-Based Smart Grid Communicationsrdquo IEEECommunications Magazine vol 55 no 10 pp 70ndash75 2017
[26] L Chen S Thombre K Jarvinen et al et al ldquoRobustnesssecurity and privacy in location-based services for future iota surveyrdquo IEEE Access vol 5 pp 8956ndash8977 2017
[27] N Saxena S Grijalva and N S Chaudhari ldquoAuthenticationprotocol for an iot-enabled LTE networkrdquoACMTransactions onInternet Technology (TOIT) vol 16 no 4 article no 25 2016
[28] M N Aman K C Chua and B Sikdar ldquoA light-weight mutualauthentication protocol for iot systemsrdquo in Proceedings of theGLOBECOM IEEE Global Communications Conference pp 1ndash6 2017
[29] N Li D Liu and S Nepal ldquoLightweight mutual authenticationfor iot and its applicationsrdquo IEEE Transactions on SustainableComputing vol 2 no 4 pp 359ndash370 2017
[30] S Sciancalepore G Piro G Boggia andG Bianchi ldquoPublic keyauthentication and key agreement in iot devices with minimalairtime consumptionrdquo IEEE Embedded Systems Letters vol 9no 1 pp 1ndash4 2017
[31] M Wazid A K Das M K Khan A A-D Al-Ghaiheb NKumar and A V Vasilakos ldquoSecure authentication scheme formedicine anti-counterfeiting system in iot environmentrdquo IEEEInternet of Things Journal vol 4 no 5 pp 1634ndash1646 2017
[32] B L Parne S Gupta and N S Chaudhari ldquoSegb Securityenhanced group based aka protocol form2mcommunication inan iot enabled ltelte-a networkrdquo IEEE Access vol 6 pp 3668ndash3684 2018
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawiwwwhindawicom Volume 2018
Hindawiwwwhindawicom Volume 2018
Navigation and Observation
International Journal of
Hindawi
wwwhindawicom Volume 2018
Advances in
Multimedia
Submit your manuscripts atwwwhindawicom
Security and Communication Networks 5
Finally a certification parameter 119877 is calculated119877 = 119902211990411198831199041 + 119909 (3)
where 1199022 is the parameter computed by KGC according tothe identity information of the receiver and 1199041 represents thesecret key of the sender which is generated by KGC
Finally the sender transmits the encrypted detectionresult119872 the certification parameter 119877 and the parameter119883to the receiver
423 Implementation Phase This phase refers to the processof the receiver accepting information and performing relatedemergence operationsThe receiver needs to first authenticatethe identity of the node sending the information
The receiver first computes a assistance parameter 119871119871 = 1199021119875pub + 1198831199042 (4)
where 1199021 is the parameter generated by KGC about theidentity information if the sender 119875pub is the public key ofsystem 119883 is the parameter sent by the sender and 1199042 is itsown private key
The parameter 1199081015840 is restored with the calculation 1199081015840 =119890(119871 119877) The message about the emergency is computed by119898 = 119872 oplus1198672(1199081015840)
Finally when obtaining the correct information thereceiver will implement related operations according to thereal-time information
5 Security Analysis
In this section the correctness of our scheme is firstly shownThen the security analysis is presented in aspects of securityagainst a forged sender MITM attack and an unregisteredreceiver
51 Correctness The correctness of a scheme is that thecalculation process of the design can eventually achieve thedesired goal and complete the expected security expectationFor the scheme we have designed correctness refers to thefact that the sender and the receiver can encrypt and decryptthe information through themethods we design respectively
We denote the new 119908 computed by the receiver as 1199081015840 1199081015840can be calculated as follows
Based on the above deduction it is not difficult to drawthe conclusion that the designed scheme is correct
52 Security against a Forged Sender An adversary maycompromise a sensor node or a detector node to send somefake alarmmessage Identity information of the sender mightbe stolen Such sender is called a forged sender
In our scheme the adversary can fake one 1205981 to replace 1199041but he knows nothing about 119905 So the adversary cannot matchhis fake 1205981 with 1199041 = 1199051198671(ID) Therefore a forged sendercannot send a 119877 that can be verified
53 Security against MITM Attack If an attacker wantsto capture or tamper with the content of the message byintercepting information he is called a man-in-the-middle
The attacker can intercept the message (119872 119877119883) of ourscheme If he wants to capture the specific message he needsto decrypt the message 119872 However he has no chance toknow about the parameter 119909 which is a random numbergenerated by the sender during every transmission It cannotbe excluded that he can break the message through thereceiver But in fact an attacker cannot know any recipientrsquosprivate key 1199042
In addition if the attacker wants to tamper with themessage he needs to generate a fake number 120575 to replacethe random number 119909 and regenerate 119877 Actually he knownothing about 1199041 so he cannot generate an effective 119877 If heeven forges 1199041 he will fall into the same embarrassment as theadversary in the previous subsection
Besides the attacker can constantly collect the encryptedmessage ciphertext and the original text sent before thesender However since 119909 is a random number which changesin every round he cannot infer the encrypted informationfrom the previous plaintext and ciphertext
54 Security against an Unregistered Receiver An unreg-istered receiver is an unlawful node but it can receiveencrypted information If the receiver is true and not reg-istered the sender will not be able to compute encryptedinformation that matches 1199022 Therefore it does not have thecorresponding 1199042 to decrypt the message
6 Performance Analysis
This section is going to discuss the performance of the pro-posed protocol The computational cost of different entitiesin the proposed scheme is shown in Table 1 We take intoconsideration the computational costs of the sender andthe receiver We consider the cost of collision-resistant hashfunction bilinear pairing scalar multiplication exclusive-OR and group exponent In Table 1 M represents scalarmultiplication P denotes bilinear pairing E refers to groupexponent H represents collision-resistant hash functionoperation and XOR denotes exclusive-OR By computationthe result comes out that a sender costs 2 scalar multiplica-tions 1 bilinear pairing 1 group exponent 1 collision-resistanthash function operations and 1 exclusive-OR for sendingthe message to one receiver In addition a receiver costs 1scalar multiplications 1 bilinear pairing 1 collision-resistanthash function operations and 1 exclusive-OR to rebuild themessage
Figure 4 The time cost of a sender when the number of receivergrows
5 10 15 20 25 30 35 40 45 500Number of Senders
0
100
200
300
400
500
600
Com
puta
tiona
l Cos
t of a
Rec
eive
r (m
s)
Figure 5 The time cost of a receiver when the number of sendergrows
The efficiency of the proposed scheme is simulated onGNU Multiple Precision Arithmetic (GMP) library andPairing-Based Cryptography (PBC) library (httpscryptostanfordedupbc) We utilize C language on a Linux systemwith Ubuntu 1604 TLS a 260GHz Intel(R) Xeon(R) CPUE5-2650 v2 and 8GB of RAM The results are illustrated inFigures 4 and 5 It is not difficult to see that both the senderrsquosand the receiverrsquos computational costs will increase as thenumber of the other party increases The increasing trend ofthe senderrsquos cost due to the increase in the number of theother party is slower Although our experiments simulate a
large number of nodes the number of nodes in a smart homenetwork is actually very limited Therefore we find that thenew scheme we propose costs very limited time to transmitemergence data Combining this scheme with efficient dataanalysis and instruction dispatching algorithms can achieveresponse to emergencies in a smart home environment
7 Conclusion
In this paper we propose a novel scheme based on instantencrypted transmission for IoT-based smart home systemThe three phases of the registration phase the detectionphase and the implementation phase constitute themain partof the overall scheme The simulation by PBC shows that ournovel scheme enables the transfer of important data in a veryshort period of time while protecting the privacy of data
Data Availability
The data used to support the findings of this study areavailable from the corresponding author upon request
Conflicts of Interest
The authors declare that they have no conflicts of interest
Acknowledgments
Thiswork is supported by theNational Natural Science Foun-dation of China under Grant no 61672295 no 61672290no U1405254 and no 61772280 the State Key Laboratory ofInformation Security under Grant no 2017-MS-10 the 2015Project of Six Personnel in Jiangsu Province under Grant noR2015L06 the CICAEET fund and the PAPD fund
References
[1] D Zhang L T Yang M Chen S Zhao M Guo and Y ZhangldquoReal-time locating systems using active rfid for internet ofthingsrdquo IEEE Systems Journal vol 10 no 3 pp 1226ndash1235 2016
[2] Z Zhou M Dong K Ota G Wang and L T Yang ldquoEnergy-efficient resource allocation for d2d communications under-laying cloud-ran-based lte-a networksrdquo IEEE Internet of ThingsJournal vol 3 no 3 pp 428ndash438 2016
[3] J Zhou Z Cao X Dong and A V Vasilakos ldquoSecurity andprivacy for cloud-based IoT challengesrdquo IEEE CommunicationsMagazine vol 55 no 1 pp 26ndash33 2017
[4] X Zhang Y Tan C Liang Y Li and J Li ldquoA covert channelover volte via adjusting silence periodsrdquo IEEE Access vol 6 pp9292ndash9302 2018
[5] J Shen T Zhou D He Y Zhang X Sun and Y XiangldquoBlock design-based key agreement for group data sharing in
Security and Communication Networks 7
cloud computingrdquo IEEE Transactions on Dependable and SecureComputing vol PP no 99 2017
[6] Q Lin J Li Z Huang W Chen and J Shen ldquoA short linearlyhomomorphic proxy signature schemerdquo IEEE Access vol 6 pp12966ndash12972 2018
[7] J Li J Li X Chen C Jia and W Lou ldquoIdentity-basedencryption with outsourced revocation in cloud computingrdquoInstitute of Electrical and Electronics Engineers Transactions onComputers vol 64 no 2 pp 425ndash437 2015
[8] Y Xiang W Zhou and M Guo ldquoFlexible deterministic packetmarking An IP traceback system to find the real source ofattacksrdquo IEEE Transactions on Parallel and Distributed Systemsvol 20 no 4 pp 567ndash580 2009
[9] J Shen T Zhou X Chen J Li and W Susilo ldquoAnonymousand traceable group data sharing in cloud computingrdquo IEEETransactions on Information Forensics and Security vol 13 no4 pp 912ndash925 2018
[10] X Chen J Li X Huang J Ma and W Lou ldquoNew PubliclyVerifiable Databases with Efficient Updatesrdquo IEEE Transactionson Dependable and Secure Computing vol 12 no 5 pp 546ndash556 2015
[11] Q Lin H Yan Z Huang W Chen J Shen and Y TangldquoAn ID-based linearly homomorphic signature scheme and itsapplication in blockchainrdquo IEEE Access vol 6 2018
[12] M Z Alam Bhuiyan J Wu G Wang and J Cao ldquoSensingand decision making in cyber-physical systems the case ofstructural event monitoringrdquo IEEE Transactions on IndustrialInformatics vol 12 no 6 pp 2103ndash2114 2016
[13] H Liu H Ning Y Zhang Q Xiong and L T Yang ldquoRole-dependent privacy preservation for secure v2 g networks inthe smart gridrdquo IEEE Transactions on Information Forensics ampSecurity vol 9 no 2 pp 208ndash220 2017
[14] J Li Y K Li X Chen P P C Lee and W Lou ldquoA hybridcloud approach for secure authorized deduplicationrdquo Parallelamp Distributed Systems IEEE Transactions on vol 26 no 5 pp1206ndash1216 2015
[15] J Shen C Wang C-F Lai A Wang and H-C Chao ldquoDirec-tion Density-Based Secure Routing Protocol for HealthcareData in Incompletely Predictable Networksrdquo IEEE Access vol4 pp 9163ndash9173 2016
[16] Y Yu M H Au G Ateniese et al ldquoIdentity-Based RemoteData Integrity Checking with Perfect Data Privacy Preservingfor Cloud Storagerdquo IEEE Transactions on Information Forensicsand Security vol 12 no 4 pp 767ndash778 2017
[17] J Shen J Shen X Chen X Huang and W Susilo ldquoAn efficientpublic auditing protocol with novel dynamic structure for clouddatardquo IEEE Transactions on Information Forensics and Securityvol 12 no 10 pp 2402ndash2415 2017
[18] P Li J Li Z Huang et al ldquoMulti-key privacy-preserving deeplearning in cloud computingrdquo Future Generation ComputerSystems vol 74 pp 76ndash85 2017
[19] T Jiang X Chen and JMa ldquoPublic integrity auditing for shareddynamic cloud data with group user revocationrdquo Institute ofElectrical and Electronics Engineers Transactions on Computersvol 65 no 8 pp 2363ndash2373 2016
[20] X Chen J Li J Weng J Ma andW Lou ldquoVerifiable computa-tion over large database with incremental updatesrdquo Institute ofElectrical and Electronics Engineers Transactions on Computersvol 65 no 10 pp 3184ndash3195 2016
[21] J Li Y Zhang X Chen and Y Xiang ldquoSecure attribute-baseddata sharing for resource-limited users in cloud computingrdquoComputersSecurity vol 72 p 12 2018
[22] J Shen D Liu J Shen Q Liu and X Sun ldquoA secure cloud-assisted urban data sharing framework for ubiquitous-citiesrdquoPervasive and Mobile Computing 2017
[23] J Yu and H Wang ldquoStrong key-exposure resilient auditingfor secure cloud storagerdquo IEEE Transactions on InformationForensics and Security vol 12 no 8 pp 1931ndash1940 2017
[24] A Sajid H Abbas and K Saleem ldquoCloud-Assisted IoT-BasedSCADA Systems Security A Review of the State of the Art andFuture Challengesrdquo IEEE Access vol 4 pp 1375ndash1384 2016
[25] W-L Chin W Li and H-H Chen ldquoEnergy Big Data SecurityThreats in IoT-Based Smart Grid Communicationsrdquo IEEECommunications Magazine vol 55 no 10 pp 70ndash75 2017
[26] L Chen S Thombre K Jarvinen et al et al ldquoRobustnesssecurity and privacy in location-based services for future iota surveyrdquo IEEE Access vol 5 pp 8956ndash8977 2017
[27] N Saxena S Grijalva and N S Chaudhari ldquoAuthenticationprotocol for an iot-enabled LTE networkrdquoACMTransactions onInternet Technology (TOIT) vol 16 no 4 article no 25 2016
[28] M N Aman K C Chua and B Sikdar ldquoA light-weight mutualauthentication protocol for iot systemsrdquo in Proceedings of theGLOBECOM IEEE Global Communications Conference pp 1ndash6 2017
[29] N Li D Liu and S Nepal ldquoLightweight mutual authenticationfor iot and its applicationsrdquo IEEE Transactions on SustainableComputing vol 2 no 4 pp 359ndash370 2017
[30] S Sciancalepore G Piro G Boggia andG Bianchi ldquoPublic keyauthentication and key agreement in iot devices with minimalairtime consumptionrdquo IEEE Embedded Systems Letters vol 9no 1 pp 1ndash4 2017
[31] M Wazid A K Das M K Khan A A-D Al-Ghaiheb NKumar and A V Vasilakos ldquoSecure authentication scheme formedicine anti-counterfeiting system in iot environmentrdquo IEEEInternet of Things Journal vol 4 no 5 pp 1634ndash1646 2017
[32] B L Parne S Gupta and N S Chaudhari ldquoSegb Securityenhanced group based aka protocol form2mcommunication inan iot enabled ltelte-a networkrdquo IEEE Access vol 6 pp 3668ndash3684 2018
Figure 4 The time cost of a sender when the number of receivergrows
5 10 15 20 25 30 35 40 45 500Number of Senders
0
100
200
300
400
500
600
Com
puta
tiona
l Cos
t of a
Rec
eive
r (m
s)
Figure 5 The time cost of a receiver when the number of sendergrows
The efficiency of the proposed scheme is simulated onGNU Multiple Precision Arithmetic (GMP) library andPairing-Based Cryptography (PBC) library (httpscryptostanfordedupbc) We utilize C language on a Linux systemwith Ubuntu 1604 TLS a 260GHz Intel(R) Xeon(R) CPUE5-2650 v2 and 8GB of RAM The results are illustrated inFigures 4 and 5 It is not difficult to see that both the senderrsquosand the receiverrsquos computational costs will increase as thenumber of the other party increases The increasing trend ofthe senderrsquos cost due to the increase in the number of theother party is slower Although our experiments simulate a
large number of nodes the number of nodes in a smart homenetwork is actually very limited Therefore we find that thenew scheme we propose costs very limited time to transmitemergence data Combining this scheme with efficient dataanalysis and instruction dispatching algorithms can achieveresponse to emergencies in a smart home environment
7 Conclusion
In this paper we propose a novel scheme based on instantencrypted transmission for IoT-based smart home systemThe three phases of the registration phase the detectionphase and the implementation phase constitute themain partof the overall scheme The simulation by PBC shows that ournovel scheme enables the transfer of important data in a veryshort period of time while protecting the privacy of data
Data Availability
The data used to support the findings of this study areavailable from the corresponding author upon request
Conflicts of Interest
The authors declare that they have no conflicts of interest
Acknowledgments
Thiswork is supported by theNational Natural Science Foun-dation of China under Grant no 61672295 no 61672290no U1405254 and no 61772280 the State Key Laboratory ofInformation Security under Grant no 2017-MS-10 the 2015Project of Six Personnel in Jiangsu Province under Grant noR2015L06 the CICAEET fund and the PAPD fund
References
[1] D Zhang L T Yang M Chen S Zhao M Guo and Y ZhangldquoReal-time locating systems using active rfid for internet ofthingsrdquo IEEE Systems Journal vol 10 no 3 pp 1226ndash1235 2016
[2] Z Zhou M Dong K Ota G Wang and L T Yang ldquoEnergy-efficient resource allocation for d2d communications under-laying cloud-ran-based lte-a networksrdquo IEEE Internet of ThingsJournal vol 3 no 3 pp 428ndash438 2016
[3] J Zhou Z Cao X Dong and A V Vasilakos ldquoSecurity andprivacy for cloud-based IoT challengesrdquo IEEE CommunicationsMagazine vol 55 no 1 pp 26ndash33 2017
[4] X Zhang Y Tan C Liang Y Li and J Li ldquoA covert channelover volte via adjusting silence periodsrdquo IEEE Access vol 6 pp9292ndash9302 2018
[5] J Shen T Zhou D He Y Zhang X Sun and Y XiangldquoBlock design-based key agreement for group data sharing in
Security and Communication Networks 7
cloud computingrdquo IEEE Transactions on Dependable and SecureComputing vol PP no 99 2017
[6] Q Lin J Li Z Huang W Chen and J Shen ldquoA short linearlyhomomorphic proxy signature schemerdquo IEEE Access vol 6 pp12966ndash12972 2018
[7] J Li J Li X Chen C Jia and W Lou ldquoIdentity-basedencryption with outsourced revocation in cloud computingrdquoInstitute of Electrical and Electronics Engineers Transactions onComputers vol 64 no 2 pp 425ndash437 2015
[8] Y Xiang W Zhou and M Guo ldquoFlexible deterministic packetmarking An IP traceback system to find the real source ofattacksrdquo IEEE Transactions on Parallel and Distributed Systemsvol 20 no 4 pp 567ndash580 2009
[9] J Shen T Zhou X Chen J Li and W Susilo ldquoAnonymousand traceable group data sharing in cloud computingrdquo IEEETransactions on Information Forensics and Security vol 13 no4 pp 912ndash925 2018
[10] X Chen J Li X Huang J Ma and W Lou ldquoNew PubliclyVerifiable Databases with Efficient Updatesrdquo IEEE Transactionson Dependable and Secure Computing vol 12 no 5 pp 546ndash556 2015
[11] Q Lin H Yan Z Huang W Chen J Shen and Y TangldquoAn ID-based linearly homomorphic signature scheme and itsapplication in blockchainrdquo IEEE Access vol 6 2018
[12] M Z Alam Bhuiyan J Wu G Wang and J Cao ldquoSensingand decision making in cyber-physical systems the case ofstructural event monitoringrdquo IEEE Transactions on IndustrialInformatics vol 12 no 6 pp 2103ndash2114 2016
[13] H Liu H Ning Y Zhang Q Xiong and L T Yang ldquoRole-dependent privacy preservation for secure v2 g networks inthe smart gridrdquo IEEE Transactions on Information Forensics ampSecurity vol 9 no 2 pp 208ndash220 2017
[14] J Li Y K Li X Chen P P C Lee and W Lou ldquoA hybridcloud approach for secure authorized deduplicationrdquo Parallelamp Distributed Systems IEEE Transactions on vol 26 no 5 pp1206ndash1216 2015
[15] J Shen C Wang C-F Lai A Wang and H-C Chao ldquoDirec-tion Density-Based Secure Routing Protocol for HealthcareData in Incompletely Predictable Networksrdquo IEEE Access vol4 pp 9163ndash9173 2016
[16] Y Yu M H Au G Ateniese et al ldquoIdentity-Based RemoteData Integrity Checking with Perfect Data Privacy Preservingfor Cloud Storagerdquo IEEE Transactions on Information Forensicsand Security vol 12 no 4 pp 767ndash778 2017
[17] J Shen J Shen X Chen X Huang and W Susilo ldquoAn efficientpublic auditing protocol with novel dynamic structure for clouddatardquo IEEE Transactions on Information Forensics and Securityvol 12 no 10 pp 2402ndash2415 2017
[18] P Li J Li Z Huang et al ldquoMulti-key privacy-preserving deeplearning in cloud computingrdquo Future Generation ComputerSystems vol 74 pp 76ndash85 2017
[19] T Jiang X Chen and JMa ldquoPublic integrity auditing for shareddynamic cloud data with group user revocationrdquo Institute ofElectrical and Electronics Engineers Transactions on Computersvol 65 no 8 pp 2363ndash2373 2016
[20] X Chen J Li J Weng J Ma andW Lou ldquoVerifiable computa-tion over large database with incremental updatesrdquo Institute ofElectrical and Electronics Engineers Transactions on Computersvol 65 no 10 pp 3184ndash3195 2016
[21] J Li Y Zhang X Chen and Y Xiang ldquoSecure attribute-baseddata sharing for resource-limited users in cloud computingrdquoComputersSecurity vol 72 p 12 2018
[22] J Shen D Liu J Shen Q Liu and X Sun ldquoA secure cloud-assisted urban data sharing framework for ubiquitous-citiesrdquoPervasive and Mobile Computing 2017
[23] J Yu and H Wang ldquoStrong key-exposure resilient auditingfor secure cloud storagerdquo IEEE Transactions on InformationForensics and Security vol 12 no 8 pp 1931ndash1940 2017
[24] A Sajid H Abbas and K Saleem ldquoCloud-Assisted IoT-BasedSCADA Systems Security A Review of the State of the Art andFuture Challengesrdquo IEEE Access vol 4 pp 1375ndash1384 2016
[25] W-L Chin W Li and H-H Chen ldquoEnergy Big Data SecurityThreats in IoT-Based Smart Grid Communicationsrdquo IEEECommunications Magazine vol 55 no 10 pp 70ndash75 2017
[26] L Chen S Thombre K Jarvinen et al et al ldquoRobustnesssecurity and privacy in location-based services for future iota surveyrdquo IEEE Access vol 5 pp 8956ndash8977 2017
[27] N Saxena S Grijalva and N S Chaudhari ldquoAuthenticationprotocol for an iot-enabled LTE networkrdquoACMTransactions onInternet Technology (TOIT) vol 16 no 4 article no 25 2016
[28] M N Aman K C Chua and B Sikdar ldquoA light-weight mutualauthentication protocol for iot systemsrdquo in Proceedings of theGLOBECOM IEEE Global Communications Conference pp 1ndash6 2017
[29] N Li D Liu and S Nepal ldquoLightweight mutual authenticationfor iot and its applicationsrdquo IEEE Transactions on SustainableComputing vol 2 no 4 pp 359ndash370 2017
[30] S Sciancalepore G Piro G Boggia andG Bianchi ldquoPublic keyauthentication and key agreement in iot devices with minimalairtime consumptionrdquo IEEE Embedded Systems Letters vol 9no 1 pp 1ndash4 2017
[31] M Wazid A K Das M K Khan A A-D Al-Ghaiheb NKumar and A V Vasilakos ldquoSecure authentication scheme formedicine anti-counterfeiting system in iot environmentrdquo IEEEInternet of Things Journal vol 4 no 5 pp 1634ndash1646 2017
[32] B L Parne S Gupta and N S Chaudhari ldquoSegb Securityenhanced group based aka protocol form2mcommunication inan iot enabled ltelte-a networkrdquo IEEE Access vol 6 pp 3668ndash3684 2018
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawiwwwhindawicom Volume 2018
Hindawiwwwhindawicom Volume 2018
Navigation and Observation
International Journal of
Hindawi
wwwhindawicom Volume 2018
Advances in
Multimedia
Submit your manuscripts atwwwhindawicom
Security and Communication Networks 7
cloud computingrdquo IEEE Transactions on Dependable and SecureComputing vol PP no 99 2017
[6] Q Lin J Li Z Huang W Chen and J Shen ldquoA short linearlyhomomorphic proxy signature schemerdquo IEEE Access vol 6 pp12966ndash12972 2018
[7] J Li J Li X Chen C Jia and W Lou ldquoIdentity-basedencryption with outsourced revocation in cloud computingrdquoInstitute of Electrical and Electronics Engineers Transactions onComputers vol 64 no 2 pp 425ndash437 2015
[8] Y Xiang W Zhou and M Guo ldquoFlexible deterministic packetmarking An IP traceback system to find the real source ofattacksrdquo IEEE Transactions on Parallel and Distributed Systemsvol 20 no 4 pp 567ndash580 2009
[9] J Shen T Zhou X Chen J Li and W Susilo ldquoAnonymousand traceable group data sharing in cloud computingrdquo IEEETransactions on Information Forensics and Security vol 13 no4 pp 912ndash925 2018
[10] X Chen J Li X Huang J Ma and W Lou ldquoNew PubliclyVerifiable Databases with Efficient Updatesrdquo IEEE Transactionson Dependable and Secure Computing vol 12 no 5 pp 546ndash556 2015
[11] Q Lin H Yan Z Huang W Chen J Shen and Y TangldquoAn ID-based linearly homomorphic signature scheme and itsapplication in blockchainrdquo IEEE Access vol 6 2018
[12] M Z Alam Bhuiyan J Wu G Wang and J Cao ldquoSensingand decision making in cyber-physical systems the case ofstructural event monitoringrdquo IEEE Transactions on IndustrialInformatics vol 12 no 6 pp 2103ndash2114 2016
[13] H Liu H Ning Y Zhang Q Xiong and L T Yang ldquoRole-dependent privacy preservation for secure v2 g networks inthe smart gridrdquo IEEE Transactions on Information Forensics ampSecurity vol 9 no 2 pp 208ndash220 2017
[14] J Li Y K Li X Chen P P C Lee and W Lou ldquoA hybridcloud approach for secure authorized deduplicationrdquo Parallelamp Distributed Systems IEEE Transactions on vol 26 no 5 pp1206ndash1216 2015
[15] J Shen C Wang C-F Lai A Wang and H-C Chao ldquoDirec-tion Density-Based Secure Routing Protocol for HealthcareData in Incompletely Predictable Networksrdquo IEEE Access vol4 pp 9163ndash9173 2016
[16] Y Yu M H Au G Ateniese et al ldquoIdentity-Based RemoteData Integrity Checking with Perfect Data Privacy Preservingfor Cloud Storagerdquo IEEE Transactions on Information Forensicsand Security vol 12 no 4 pp 767ndash778 2017
[17] J Shen J Shen X Chen X Huang and W Susilo ldquoAn efficientpublic auditing protocol with novel dynamic structure for clouddatardquo IEEE Transactions on Information Forensics and Securityvol 12 no 10 pp 2402ndash2415 2017
[18] P Li J Li Z Huang et al ldquoMulti-key privacy-preserving deeplearning in cloud computingrdquo Future Generation ComputerSystems vol 74 pp 76ndash85 2017
[19] T Jiang X Chen and JMa ldquoPublic integrity auditing for shareddynamic cloud data with group user revocationrdquo Institute ofElectrical and Electronics Engineers Transactions on Computersvol 65 no 8 pp 2363ndash2373 2016
[20] X Chen J Li J Weng J Ma andW Lou ldquoVerifiable computa-tion over large database with incremental updatesrdquo Institute ofElectrical and Electronics Engineers Transactions on Computersvol 65 no 10 pp 3184ndash3195 2016
[21] J Li Y Zhang X Chen and Y Xiang ldquoSecure attribute-baseddata sharing for resource-limited users in cloud computingrdquoComputersSecurity vol 72 p 12 2018
[22] J Shen D Liu J Shen Q Liu and X Sun ldquoA secure cloud-assisted urban data sharing framework for ubiquitous-citiesrdquoPervasive and Mobile Computing 2017
[23] J Yu and H Wang ldquoStrong key-exposure resilient auditingfor secure cloud storagerdquo IEEE Transactions on InformationForensics and Security vol 12 no 8 pp 1931ndash1940 2017
[24] A Sajid H Abbas and K Saleem ldquoCloud-Assisted IoT-BasedSCADA Systems Security A Review of the State of the Art andFuture Challengesrdquo IEEE Access vol 4 pp 1375ndash1384 2016
[25] W-L Chin W Li and H-H Chen ldquoEnergy Big Data SecurityThreats in IoT-Based Smart Grid Communicationsrdquo IEEECommunications Magazine vol 55 no 10 pp 70ndash75 2017
[26] L Chen S Thombre K Jarvinen et al et al ldquoRobustnesssecurity and privacy in location-based services for future iota surveyrdquo IEEE Access vol 5 pp 8956ndash8977 2017
[27] N Saxena S Grijalva and N S Chaudhari ldquoAuthenticationprotocol for an iot-enabled LTE networkrdquoACMTransactions onInternet Technology (TOIT) vol 16 no 4 article no 25 2016
[28] M N Aman K C Chua and B Sikdar ldquoA light-weight mutualauthentication protocol for iot systemsrdquo in Proceedings of theGLOBECOM IEEE Global Communications Conference pp 1ndash6 2017
[29] N Li D Liu and S Nepal ldquoLightweight mutual authenticationfor iot and its applicationsrdquo IEEE Transactions on SustainableComputing vol 2 no 4 pp 359ndash370 2017
[30] S Sciancalepore G Piro G Boggia andG Bianchi ldquoPublic keyauthentication and key agreement in iot devices with minimalairtime consumptionrdquo IEEE Embedded Systems Letters vol 9no 1 pp 1ndash4 2017
[31] M Wazid A K Das M K Khan A A-D Al-Ghaiheb NKumar and A V Vasilakos ldquoSecure authentication scheme formedicine anti-counterfeiting system in iot environmentrdquo IEEEInternet of Things Journal vol 4 no 5 pp 1634ndash1646 2017
[32] B L Parne S Gupta and N S Chaudhari ldquoSegb Securityenhanced group based aka protocol form2mcommunication inan iot enabled ltelte-a networkrdquo IEEE Access vol 6 pp 3668ndash3684 2018
