Presented at the International Workshop on Research Challenges in Security and Privacy for Mobile and Wireless Networks (WSPWN 2006), Miami, Florida, March 15-16, 2006 CS 6910: Advanced Computer and Information Security CS 6910: Advanced Computer and Information Security Lecture 2b Lecture 2b Opportunistic Opportunistic Networks: Networks: The Concept and Research The Concept and Research Challenges Challenges in Privacy and in Privacy and Security Security Leszek Lilien, Zille Huma Kamal Leszek Lilien, Zille Huma Kamal , Vijay Bhuse , Vijay Bhuse and and Ajay Gupta Ajay Gupta WiSe (Wi WiSe (Wi reless Sensornet reless Sensornet s) s) Lab Lab http://www.cs.wmich.edu/wsn Department of Computer Science Department of Computer Science Western Michigan University Western Michigan University Kalamazoo, MI 49008 Kalamazoo, MI 49008
Transcript
Presented at the International Workshop on Research Challenges in Security and Privacy for Mobile and Wireless Networks (WSPWN 2006), Miami, Florida,
March 15-16, 2006
CS 6910: Advanced Computer and Information SecurityCS 6910: Advanced Computer and Information SecurityLecture 2bLecture 2b
Opportunistic Opportunistic Networks:Networks:The Concept and Research The Concept and Research
Challenges Challenges in Privacy and Securityin Privacy and Security
Leszek Lilien, Zille Huma KamalLeszek Lilien, Zille Huma Kamal, Vijay Bhuse, Vijay Bhuse and Ajay Gupta and Ajay Gupta
Department of Computer ScienceDepartment of Computer ScienceWestern Michigan UniversityWestern Michigan University
Kalamazoo, MI 49008Kalamazoo, MI 49008
March 15-16, 2006
> CS 6910: Go to Slide 15 <> CS 6910: Go to Slide 15 <
Basic Concepts for Opportunistic NetworksBasic Concepts for Opportunistic Networks
New paradigm and technology:New paradigm and technology:opportunistic networks opportunistic networks oror oppnets oppnets
IInnovativennovative Facing Facing thethe challenge ofchallenge of pervasivepervasive ccomputingomputing AdvancingAdvancing leading-edge leading-edge pervasive computing and networking pervasive computing and networking
know-howknow-how
Oppnet deployed as a Oppnet deployed as a seed oppnetseed oppnet Localizes its nodesLocalizes its nodes Configures itselfConfigures itself Adapts to environmentAdapts to environment 2
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Startup: Seed OppnetStartup: Seed Oppnet
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Oppnet starts as a Oppnet starts as a seedseed oppnetoppnet
Seed oppnet grows into an Seed oppnet grows into an expandedexpanded oppnetoppnet
Seed Nodes
Link tothe World
Controller (distributed)
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Growth: Expanded OppnetGrowth: Expanded Oppnet
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HeterogenousHeterogenous helpers helpers join oppnet join oppnet Add communication, computing, sensing, storage, other resourcesAdd communication, computing, sensing, storage, other resources
BenevolentBenevolent OppnetOppnetScenario: „Citizens Scenario: „Citizens Called to Arms” (1)Called to Arms” (1) SeedSeed oppnet oppnet deployeddeployed
afterafter an an earthquakeearthquake (un-(un-predictable emergency)predictable emergency) Seed is aSeed is ad hocd hoc wireless wireless netnetworkwork with with very very
powerful nodespowerful nodes MMore energy, computing and communication resourcesore energy, computing and communication resources
SSeed tries to eed tries to detect detect candidate helperscandidate helpers For For help in damage assessment and disaster help in damage assessment and disaster
recoveryrecovery UUses any available detection methodses any available detection method — including: — including:
Celphone- Celphone- oror radio radio-based detection-based detection SSearching for nodes using the earching for nodes using the IP addressIP address range for the range for the
BenevolentBenevolent OppnetOppnetScenario: „Citizens Scenario: „Citizens Called to Arms” (2)Called to Arms” (2)
Example:Example: Helper 1 monitoring a surveillance net detects Helper 1 monitoring a surveillance net detects
an overturned caran overturned car Helper 2 asked to recognize its license plateHelper 2 asked to recognize its license plate Helper 3 finds that the cars has Helper 3 finds that the cars has OnStarOnStar linklink Helper 4Helper 4 contactscontacts BANs BANs (Body Area Network)(Body Area Network) on or on or
within bodies of car occupants via OnStar within bodies of car occupants via OnStar infrastructureinfrastructure
Helper 5 evaluates obtained info and dispatches Helper 5 evaluates obtained info and dispatches rescuersrescuers
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BenevolentBenevolent OppnetOppnetScenario: Scenario: „Citizens Called to „Citizens Called to Arms” (3)Arms” (3)
Oppnet selects Oppnet selects optimaloptimal subset of detectedsubset of detected nodes nodes Inviting Inviting devices, clustersdevices, clusters & & entire net entire networkworkss Helpers forHelpers for communicating communicating, , sensingsensing, , computingcomputing
Using Using „hidden” capabilities„hidden” capabilities, e.g. for sensing:, e.g. for sensing: Desktop can Desktop can „sense” presence„sense” presence of a potential of a potential
victim at its keyboardvictim at its keyboard CCellphones ellphones can can „sense” location„sense” location
Even ones w/o GPS can be triangulatedEven ones w/o GPS can be triangulated
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Using „hidden”Using „hidden”emergency functionalitiesemergency functionalities Oppnet Oppnet contactcontacts 2 s 2 independent sensornetsindependent sensornets
(SNs):(SNs):
water infrastructure controlwater infrastructure control SN / SN / public space surveillancepublic space surveillance SN SN
SNsSNs ordered ordered to abandon normal functionsto abandon normal functions & & help inhelp in rescue & recovery operationsrescue & recovery operations WWater infrastructure ater infrastructure SNSN ((with multisensor with multisensor
capabilitiescapabilities, , under road surfaces)under road surfaces) — — ordered ordered to to sense vehicular movement and traffic jamssense vehicular movement and traffic jams
PPublic space surveillance ublic space surveillance SNSN — — ordered ordered to to search for images of human victimssearch for images of human victims
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Benevolent Benevolent OppnetOppnetScenario: Scenario: „Citizens Called to „Citizens Called to Arms” (4)Arms” (4)
Scenario 1 — TerroristsScenario 1 — Terroristscreatecreate apparentlyapparently harmless harmless weather weather monito-monito-ring ring sensornetsensornet (SN): (SN): SNSN becomes a seed of a becomes a seed of a malevolentmalevolent
opportunistic opportunistic SNSN SN exploitsSN exploits other nodes from many other other nodes from many other
networksnetworks (w/o revealing its true goals)(w/o revealing its true goals) ““CCritical mass” ritical mass” of the of the opportunistic opportunistic SNSN is reached is reached ((in in
terms of geographical spread and terms of geographical spread and sensing sensing capabilitiescapabilities))
SN SN waits for waits for wind patterns that can wind patterns that can speed upspeed up spread of poisonous chemicalsspread of poisonous chemicals CCollected data used to deciollected data used to decide when to de when to start chemicalstart chemical
attackattack
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MalevolentMalevolent Oppnet Scenario:Oppnet Scenario:„Bad Guys Gang Up” (2)„Bad Guys Gang Up” (2)
Scenario 2 — network at home starts spying on you:Scenario 2 — network at home starts spying on you: Becomes a seed oppnetBecomes a seed oppnet Exploits other devices/nets to collect all info on you:Exploits other devices/nets to collect all info on you:
From your From your fridgefridge (& RFID-equipped food packaging)(& RFID-equipped food packaging): : what/when you eatwhat/when you eat
From your From your computercomputer: keylogs your passwords, sensitive : keylogs your passwords, sensitive datadata
From your From your cellphonecellphone: who you call & when: who you call & when From your networked From your networked cameracamera: what photos you take: what photos you take From your home From your home security surveillancesecurity surveillance system: your system: your
private imagesprivate images CyberflyCyberfly with camera eyes and microphone ears with camera eyes and microphone ears ......
Among wireless networks: WANs, MANs, LANs, PANs Among wireless networks: WANs, MANs, LANs, PANs (personal)(personal)
MMuch less research on interoperability between wired uch less research on interoperability between wired && wireless wireless netsnets
Ambient networks Ambient networks (big European Union project, next-generation (big European Union project, next-generation Internet—for 2015/2020, smaller networks able to compose Internet—for 2015/2020, smaller networks able to compose themselves into bigger ones)themselves into bigger ones)
Growth in Growth in P2PP2P ssystems ystems SSearching for peers in unstructured systemsearching for peers in unstructured systems
GridGrid Systems Systems Integrating and managing heterogeneous systemsIntegrating and managing heterogeneous systems
Trojan HorsesTrojan Horses MimicMimic their spread capabilities their spread capabilities in search for helpers in search for helpers
OtherOther13
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Research Challenges in Basic Research Challenges in Basic OperationsOperations
BypassedBypassed in this presentation in this presentation Include:Include:
Challenges inChallenges in DetectDetectinging Helper SystemsHelper Systems E.g., E.g., primitivesprimitives to detect to detect candidates, icandidates, identify and categorize dentify and categorize
them, evaluate and cthem, evaluate and classify lassify them (e.g., bthem (e.g., based on dependability ased on dependability and usefulnessand usefulness))
E.g., selectE.g., select candidates to invite candidates to invite, d, develop evelop protocols for protocols for candidates candidates to accept or reject invitationto accept or reject invitation, d, devise primitivesevise primitives /methods to manage expanded oppnet/methods to manage expanded oppnet
Etc., etc. forEtc., etc. for remaining operations remaining operations
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> CS 6910: Start here <> CS 6910: Start here <
Research Challenges inResearch Challenges in Security and Security and PrivacyPrivacy
1) Major p1) Major prrivacy challengesivacy challenges in oppnets in oppnets
2) Security2) Security challengeschallenges in oppnets in oppnets With secondary privacy challengesWith secondary privacy challenges
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Major Privacy Challenges Major Privacy Challenges (1)(1)
PrPrivacy challengesivacy challenges in oppnets in oppnets Oppnets are and use pervasive systemsOppnets are and use pervasive systems
Must face all privacy challenges inherent to pervasive Must face all privacy challenges inherent to pervasive computingcomputing
„„Make it or break it” issue for oppnets Make it or break it” issue for oppnets (and perv. comp)(and perv. comp)
Major pMajor privacy rivacy goalsgoals Assure privacy of Assure privacy of communicationcommunicationss and and data storagedata storage Protect Protect helperhelper resources from the host oppnet resources from the host oppnet Protect Protect oppnetoppnet from its helpers from its helpers Protect Protect environmentenvironment from privacy violations by from privacy violations by
oppnetoppnet Also from malevolent oppnetsAlso from malevolent oppnets
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Major Privacy Challenges Major Privacy Challenges (2)(2) Classes of Classes of solutionssolutions to achieve the privacy goals to achieve the privacy goals
Provide Provide protected private areasprotected private areas within seed nodes/helpers within seed nodes/helpers AnonymizeAnonymize or or pseudonimizepseudonimize entities within oppnet range entities within oppnet range Detect and neutralize malevolent oppnetsDetect and neutralize malevolent oppnets Detect and neutralize exploiting oppnets for privacy Detect and neutralize exploiting oppnets for privacy
violationsviolations
Special solutionsSpecial solutions for emergency oppnet applications for emergency oppnet applications Strict Strict privacy protection relaxedprivacy protection relaxed in life-or-death situations in life-or-death situations
Must follow law and ethicsMust follow law and ethics Basic assumptionsBasic assumptions::
EEntity giventity givess up only as much privacy as indispensable for up only as much privacy as indispensable for becoming a helperbecoming a helper
EEntity’s privacy disclosure ntity’s privacy disclosure isis proportional t proportional to:o: BBenefits for the entityenefits for the entity, , or or AA broader common good broader common good
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Security Challenges Security Challenges (1)(1) SourcesSources of security challenges of security challenges
Dependable aDependable authentication cannotuthentication cannot be performed be performed when when helpershelpers join join oppnetoppnet
NNot possible to ot possible to guaranteeguarantee that malicious devices will not that malicious devices will not joinjoin
Can detect notorius behavior after entity becomes Can detect notorius behavior after entity becomes a helpera helper
If available, reputation can be used beforehandIf available, reputation can be used beforehand Delivering secret keys securely to all Delivering secret keys securely to all and only and only non-non-
malicious devices is very difficultmalicious devices is very difficult RRelying alone on cryptoelying alone on crypto authentication mechanisms authentication mechanisms (e.g., (e.g.,
Kerberos)Kerberos) not sufficient not sufficient
=>=> security challengessecurity challenges in oppnetsin oppnets are are biggerbigger Incl. Incl. MITM, packet dropping, ID spoofing MITM, packet dropping, ID spoofing
(masquerading), DoS(masquerading), DoS18
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The major security (and privacy) The major security (and privacy) challengeschallenges:: Secure routing via iSecure routing via increasing trustncreasing trust
Routing through more trusted systemsRouting through more trusted systems SharedShared secrets secrets forfor each each communicating communicating pair pair Using shared secrets with broadcast authentication Using shared secrets with broadcast authentication Using digital signatureUsing digital signaturess ……
Helper privacy and oppnet privacyHelper privacy and oppnet privacy via intrusion via intrusion detection detection (also above)(also above)
Protecting data privacyProtecting data privacy and data and data integrityintegrity Identifying Identifying and preventing and preventing most dangerous most dangerous
Secure routing via iSecure routing via increasncreased ed trusttrust Maintain Maintain list list of “more trusted”of “more trusted” entitiesentities and and list of „less list of „less
trusted”trusted” entities entities Secure routing can use both listsSecure routing can use both lists
Secure Secure wireless ad hoc wireless ad hoc routing protocol routing protocol most most relevantrelevant for opnets: for opnets: AriadneAriadne [Hu[Hu, , PePerrig, and Johnson, rrig, and Johnson, 202002]02] OOn-demand protocoln-demand protocol WWorks in the presence of compromised nodesorks in the presence of compromised nodes UUses symmetric cryptographyses symmetric cryptography AAuthenticates routing messagesuthenticates routing messages
SStill, till, cannot use directlycannot use directly MoreMore heterogeneous heterogeneous (esp. w.r.t. (esp. w.r.t. wired wired//wireless transmission wireless transmission
media)media)
Can look for Can look for less energy-efficientless energy-efficient oppnet oppnet solutionssolutions CCan rely on growth to amass needed resources (even with a an rely on growth to amass needed resources (even with a
big safety margin)big safety margin)20
SSecure ecure RRoutingouting via Increased Trust via Increased Trust
2nd line of privacy defense2nd line of privacy defense Meant to work by scaring away attackersMeant to work by scaring away attackers
More difficult than in many other netsMore difficult than in many other nets Bec. of heterogeneity, spontaneous growthBec. of heterogeneity, spontaneous growth
Catches helpers that become attackersCatches helpers that become attackers
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Helper Helper PPrivacy and rivacy and OOppnet ppnet PPrivacyrivacyvia Intrusion Detectionvia Intrusion Detection
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Data privacy Data privacy challengeschallenges CCapture of even a single apture of even a single oppnet entityoppnet entity (especially (especially
in crisis when providing physical protection is even more in crisis when providing physical protection is even more difficult)difficult) cripples cripples whole symmetric key whole symmetric key cryptography scheme cryptography scheme
Attacker masquerading as controller Attacker masquerading as controller (or cluster (or cluster
head)head) can distribute its own crypto keys can distribute its own crypto keys
Data integrity Data integrity challengeschallenges Digital signatures are expensive Digital signatures are expensive
computationally for lightweight devices computationally for lightweight devices (cellphone, PDA, etc.)(cellphone, PDA, etc.)
Packet format convesrsions can be attackedPacket format convesrsions can be attacked Heterogeneous entities/media fragment/aggregate Heterogeneous entities/media fragment/aggregate
packetspackets 22
Protecting Protecting DData ata PPrivacyrivacy and Data and Data IntegrityIntegrity
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MITMMITM: : e.g.,e.g., malicious device malicious device becomes a MITM on the becomes a MITM on the communication line between a victim and first communication line between a victim and first respondersresponders Solution: Solution: Use mutliple, heterogenous routes between victim Use mutliple, heterogenous routes between victim
and the center forredundant messageand the center forredundant message
Packet droppingPacket dropping: : e.g., e.g., malicious device dropmalicious device dropss some some packets between packets between a victima victim and the and the centercenter Solution: Solution: As above As above (will(will work if no adversary on at work if no adversary on at ≥ ≥ one one
route)route)
DoS attacksDoS attacks: : e.g., flooding emergency center with e.g., flooding emergency center with ffalse requests for helpalse requests for help SolutionSolution: L: Limit number of requests any device can generate.imit number of requests any device can generate.
„Call back” „Call back” the the victimvictim to confirm to confirm herher emergency request. emergency request.
OtherOther: : DoS attacks on weak linksDoS attacks on weak links,, ID spoofing ID spoofing, ..., ... 23
Identifying Identifying and Preventing Mand Preventing MostostDDangerous angerous AAttacksttacks - - Examples Examples
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MotivationMotivation – Why needed? – Why needed?
When prevention failsWhen prevention fails Lack of initial authentication mechanismLack of initial authentication mechanism
ChallengesChallenges:: Securely distributing informationSecurely distributing information about about
malicious entities in the presence of malicious entities in the presence of other other (unknown) (unknown) malicious entitiesmalicious entities
AAvoiding voiding maliciousmalicious entities while maintaining entities while maintaining connectivityconnectivity
Real-time Real-time iintrusion detectionntrusion detection and response and response more more difficultdifficult than in other networks than in other networks typestypes Bec. Bec. highly heterogeneoushighly heterogeneous 24
Intrusion Intrusion DDetectionetection (1) (1)
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Possible intrusion detection approach: Possible intrusion detection approach: [Zamboni, 2001][Zamboni, 2001]
Internal „Internal „software sensorssoftware sensors” used as embedded ” used as embedded detectorsdetectors
IIntrusion detection performntrusion detection performed by aed by autonomous utonomous agents using agents using embedded detectorsembedded detectors
BenefitsBenefits of e of embedded detectorsmbedded detectors:: MMore resistant to tampering or disabling, because ore resistant to tampering or disabling, because
they are a part of the program they monitor. they are a part of the program they monitor. VVery low CPU overheadery low CPU overhead ( (not executing continuouslynot executing continuously)) PPerform direct monitoring have access to the erform direct monitoring have access to the
internal data of programs they monitorinternal data of programs they monitor)) Detection dDetection data ata is safer—is safer—does not travel through an does not travel through an
external path external path (a log file, for example)(a log file, for example) between its between its generation and its usegeneration and its use
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Intrusion Intrusion DDetectionetection (2) (2)
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ConclusionsConclusions
Oppnets are a Oppnets are a new wide category of networksnew wide category of networks Leverage resources Leverage resources they can detect in the vicinitythey can detect in the vicinity
SSensing ensing / / monitoringmonitoring / / computingcomputing / / communication communication / etc. / etc. resourcesresources
Particularly well suited to Particularly well suited to emergency operationsemergency operations Starts with a buildup of communications infrastructureStarts with a buildup of communications infrastructure Applicable for Applicable for non-emergency non-emergency situations as well situations as well
High-payoff High-payoff potentialpotential for this paradigm/technology for this paradigm/technology RReduction of human suffering & loss of lifeeduction of human suffering & loss of life EEconomic conomic benefitsbenefits Technological, educational & research benefitsTechnological, educational & research benefits
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Future WorkFuture Work
IInvestigatinvestigating ng oppnetoppnet fundamentalfundamentalss
DDesigning oppnet esigning oppnet architecturearchitecture With itsWith its associated components associated components
MMethods, protocols, and algorithmsethods, protocols, and algorithms
Building a Building a prototypeprototype For sFor stimulation and timulation and feedbackfeedback
NNecessary for fine-tuning ecessary for fine-tuning oppnet designoppnet design Proof of conceptProof of concept: : technical prowess & economic technical prowess & economic
benefitsbenefits
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Thank you very muchThank you very muchfor your time and attention!for your time and attention!
* Directly related to oppnets* Directly related to oppnets
1.1. L. Lilien and A. Gupta, ” Opportunistic Networks L. Lilien and A. Gupta, ” Opportunistic Networks for Emergency Preparadness and Response” (for Emergency Preparadness and Response” (submisubmitted).tted). (*)(*)
2.2. V. Bhuse, A. Gupta, and L. Lilien, "Research challenges in lightweight intrusion detection for sensornets" V. Bhuse, A. Gupta, and L. Lilien, "Research challenges in lightweight intrusion detection for sensornets" ((submisubmitted).tted).
3.3. L. Lilien and B. Bhargava, ”A Scheme for Privacy-preserving Data Dissemination,” L. Lilien and B. Bhargava, ”A Scheme for Privacy-preserving Data Dissemination,” IEEE Transactions on Systems, Man and IEEE Transactions on Systems, Man and CyberneticsCybernetics (to appear). (to appear).
4.4. L. Lilien, Z. Kamal, V. Bhuse and A. Gupta, "Opportunistic Networks: The Concept and Research ChallengesL. Lilien, Z. Kamal, V. Bhuse and A. Gupta, "Opportunistic Networks: The Concept and Research Challenges in Privacy and in Privacy and Security,” Security,” International Workshop on Research Challenges in Security and Privacy for Mobile and Wireless NetworksInternational Workshop on Research Challenges in Security and Privacy for Mobile and Wireless Networks ( (WSPWNWSPWN 20200606), Miami, Florida, March 2006), Miami, Florida, March 2006. (*). (*)
5.5. T. Canli, M. Terwilliger, A. Gupta and A. Khokhar, "Power Efficient Algorithms for Computing Fast Fourier Transform over T. Canli, M. Terwilliger, A. Gupta and A. Khokhar, "Power Efficient Algorithms for Computing Fast Fourier Transform over Wireless Sensor NetworksWireless Sensor Networks,," " The Fourth ACS/IEEE Conference on Computer Systems and ApplicationsThe Fourth ACS/IEEE Conference on Computer Systems and Applications, Dubai, UAE, March 2006. , Dubai, UAE, March 2006.
6.6. V. Bhuse, A. Gupta and L. Lilien, "DPDSN: Detection of packet-dropping attacks for wireless sensor networksV. Bhuse, A. Gupta and L. Lilien, "DPDSN: Detection of packet-dropping attacks for wireless sensor networks,," " Proceedings of Proceedings of the the 4th4th International Trusted Internet Workshop (TIW) International Trusted Internet Workshop (TIW), , International Conference on High Performance ComputingInternational Conference on High Performance Computing, Goa, India, , Goa, India, December 2005. December 2005.
7.7. A. Gupta and V. Bhuse, "Anamoly Intrusion Detection in Wireless Sensor NetworksA. Gupta and V. Bhuse, "Anamoly Intrusion Detection in Wireless Sensor Networks,," " Journal of High Speed NetworksJournal of High Speed Networks, vol. 15, , vol. 15, issue 1, January-March 2006. issue 1, January-March 2006.
8.8. M. Terwilliger, A. Gupta, A. Khokhar and G. Greenwood,M. Terwilliger, A. Gupta, A. Khokhar and G. Greenwood, "Localization using Evolution Strategies in Sensornets"Localization using Evolution Strategies in Sensornets,," " Proceedings of Proceedings of the IEEE Congress on Evolutionary Computationthe IEEE Congress on Evolutionary Computation, Edinburgh, UK, Edinburgh, UK,, September 2005. September 2005.
9.9. V. Bhuse, A. Gupta, M. Terwilliger, Z. Yang and Z. Kamal, "Using Routing Data for Information Authentication in Sensor V. Bhuse, A. Gupta, M. Terwilliger, Z. Yang and Z. Kamal, "Using Routing Data for Information Authentication in Sensor NetworksNetworks,," " Proceedings of the 3rd International Trusted Internet Workshop (TIW)Proceedings of the 3rd International Trusted Internet Workshop (TIW), , International Conference on High International Conference on High Performance ComputingPerformance Computing, Bangalore, India, December 2004. , Bangalore, India, December 2004.
10.10. T. Canli, M. Terwilliger, A. Gupta and A. Khokhar, "Power-Time Efficient Algorithm for Computing FFT in Sensor NetworksT. Canli, M. Terwilliger, A. Gupta and A. Khokhar, "Power-Time Efficient Algorithm for Computing FFT in Sensor Networks,," " (E(Extended Abstractxtended Abstract)). . Proceedings of the Second ACM Conference on Embedded Networked Sensor SystemsProceedings of the Second ACM Conference on Embedded Networked Sensor Systems ( (SenSysSenSys), ), Baltimore, Maryland, November 2004.Baltimore, Maryland, November 2004.
11.11. B. Bhargava, L. Lilien, A. Rosenthal, and M. Winslett, “PervasiveTrust,” B. Bhargava, L. Lilien, A. Rosenthal, and M. Winslett, “PervasiveTrust,” IEEE Intelligent SystemsIEEE Intelligent Systems, vol. 19(5), Sep./Oct.2004, pp. , vol. 19(5), Sep./Oct.2004, pp. 74-77. 74-77. (*)(*)
12.12. B. Bhargava and L. Lilien, “Private and Trusted Collaborations,” B. Bhargava and L. Lilien, “Private and Trusted Collaborations,” Proc. Secure Knowledge Management (SKM 2004): A WorkshopProc. Secure Knowledge Management (SKM 2004): A Workshop, , Amherst, NY, Sep. 2004.Amherst, NY, Sep. 2004.
13.13. M. Jenamani, L. Lilien, and B. Bhargava, “Anonymizing Web Services Through a Club Mechanism with Economic Incentives,” M. Jenamani, L. Lilien, and B. Bhargava, “Anonymizing Web Services Through a Club Mechanism with Economic Incentives,” Proc. International Conference on Web Services (ICWS 2004)Proc. International Conference on Web Services (ICWS 2004), San Diego, California, July 2004, pp. 792-795., San Diego, California, July 2004, pp. 792-795.
14.14. Z. Kamal, M. Salahuddin, A. Gupta, M. Terwilliger, V. Bhuse and B. Beckmann, "Analytical Analysis of Data and Decision Fusion Z. Kamal, M. Salahuddin, A. Gupta, M. Terwilliger, V. Bhuse and B. Beckmann, "Analytical Analysis of Data and Decision Fusion in Sensor Networksin Sensor Networks,," " TThe 2004 International Conference on Embedded Systems and Applicationshe 2004 International Conference on Embedded Systems and Applications. Las Vegas, June 2004.. Las Vegas, June 2004.
15.15. M. Terwilliger, A. Gupta, V. Bhuse, Z. Kamal, and M. Salahuddin, "A Localization System M. Terwilliger, A. Gupta, V. Bhuse, Z. Kamal, and M. Salahuddin, "A Localization System UUsing Wireless Sensor Networks: A sing Wireless Sensor Networks: A Comparison of Two TechniquesComparison of Two Techniques,," " Proceedings of the 2004 Workshop on Positioning, Navigation and CommunicationProceedings of the 2004 Workshop on Positioning, Navigation and Communication, Hanover, , Hanover, Germany, March 2004 , Germany, March 2004 , pp.pp. 95-100. 95-100.
16.16. V. Bhuse, A. Gupta and R. Pidva, "A Distributed Approach to Security in SensornetsV. Bhuse, A. Gupta and R. Pidva, "A Distributed Approach to Security in Sensornets,," " The 58th IEEE Semiannual Vehicular The 58th IEEE Semiannual Vehicular Technology ConferenceTechnology Conference, Orlando, Florida, USA, Orlando, Florida, USA, , October 2003.October 2003.
17.17. L. Lilien, “Developing Pervasive Trust Paradigm for Authentication and Authorization,” L. Lilien, “Developing Pervasive Trust Paradigm for Authentication and Authorization,” Proc. Third Cracow Grid Workshop Proc. Third Cracow Grid Workshop (CGW’03)(CGW’03), Kraków (Cracow), Poland, October 2003, pp. 42-49 (invited paper)., Kraków (Cracow), Poland, October 2003, pp. 42-49 (invited paper).
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WiSe Lab Experience in Sensornets WiSe Lab Experience in Sensornets – Selected Projects Since 1/03– Selected Projects Since 1/03
* Results useful for oppnets* Results useful for oppnets
DesignDesigninging of of WiSe WiSe Security Protocols: DSPSSecurity Protocols: DSPS Location Tracker Location Tracker UUsing Motessing Motes (*) (*) RHS: RHS: Remote Home SurveillanceRemote Home Surveillance (*) (*) Directed Diffusion: Attacks & CountermeasuresDirected Diffusion: Attacks & Countermeasures Improving the Accuracy of Improving the Accuracy of Mote Mote MeasurementsMeasurements
by by UUsingsing Neural NetNeural Networkworkss SOMS: SOMS: Smart Occupancy Monitoring System Smart Occupancy Monitoring System UUsing Motessing Motes (*) (*) Comparative Study of Network SimulatorsComparative Study of Network Simulators CollaborativeCollaborative Image Processing Image Processing (*) (*) DENSe: a Development Environment for Networked SensorsDENSe: a Development Environment for Networked Sensors Incorporating Incorporating MMobile-ware in obile-ware in DDistributed istributed CComputations / omputations / GGridrids s
(*)(*) ExtendExtendinging the the ns-2 ns-2 Simulator Simulator to to SSatellite and WCN atellite and WCN SSimulationimulationss Smart Smart AAntennas for WCNsntennas for WCNs Energy Energy EEfficient MAC fficient MAC PProtocols for IEEE 802.11xrotocols for IEEE 802.11x A Wireless Security Testing SystemA Wireless Security Testing System (*) (*) Mobile and Self-Mobile and Self-CCalibrating Irrigation Systemalibrating Irrigation System Collective Collective CCommunications for ommunications for SSensornetsensornets (*) (*) 30
