Intelligence Techniques for e-government applications

8/9/2019 Intelligence Techniques for e-government applications

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International Journal of EmergingTrends & Technology in Computer Science(IJETTCS)Web Site: www.ijettcs.org Email: [email protected]

Volume 4, Issue 2, March-April 2015 ISSN 2278-6856

Volume 4, Issue 2, March – April 2015 Page 6

Abstract

This paper introduces intelligence security strategy approaches. The successful implementation of the e- government depends on the viable security. E-government security is considered one of the crucial factors for achieving an advanced stage of e-government. In this research we focused on several techniques, algorithms, approaches and different areas of data mining technique models in CyberSecurity from different perspectives, to establish a

classification and comparison of various types of Intrusion Detection and Countermeasures in E-government of this researches, Intelligent Technique Approaches categorization that reflect the important criteria of the data mining models. It summarizes various Intelligent Data analyses and presents an Intelligent Data Analysis of “Cairo Cleaning and Beautification Agency”; establishing such a classificationimpacts deeply guiding data mining applications towards

better operations and performance. Moreover how data mining can help in detection and prevention of these attacks. Information security violations such as access controlviolations as well as a discussion of various threats are

presented. Finally we present a comparative analysis between selected models to improve security. Keywords: E-government, Cyber Security models,Intrusion detection (ID), Penetration testing, Neural Networks, Fuzzy Logic, Genetic algorithm

1. INTRODUCTION The field of Artificial Intelligence has found manyapplications in the operation of power systems. Theseapplications range from Expert Systems to assist withnetwork fault diagnosis and rectification to Artificial Neural Networks and Fuzzy Logic to provide models forcomplex non-linear control problems.Intrusion detection (ID) has become a critical Componentof network administration due to the vast number ofattacks persistently threaten our computers. Traditionalintrusion detection systems are limited and do not providea complete solution for the problem. Security is animportant issue for the future of the cyberspace; due toaccess of malicious data in internet and in system securitythat controls real time data and leads to huge dimensional problems, so a data pre-processing is necessary. Attacksagainst the computer infrastructures are becoming an

increasingly serious problem. Hacking is the act of

breaking into another system with or without the owner’sknowledge. Intruders have promoted themselves andinvented innovative tools that support various types ofnetwork attacks. Hence, effective methods for intrusiondetection (ID) have become an insisting need to protectour computers from intruders. In general, there are twotypes of Intrusion Detection Systems (IDS); misusedetection systems and anomaly detection systems [1, 2,and 3].Over the past few years, there has been tremendousincrease in the cyber threats due to penetration of newtechnologies within the global economy as it involvesheavy usage/dependency of the Internet to carry out businesses for personal/business/governmental sectors.E-government- can be defined as ‘the use of informationand communication technologies, and particularly theinternet, as a tool to achieve better government’ (OECD,2003), Electronic Government constitutes the PublicAdministration that uses Information technology in orderto convert its Internal and External relations (United Nations, 2008).Applying Data Mining (DM) techniques on networktraffic data is a promising solution that helps indeveloping better intrusion detection systems. Datamining is defined as the identification of interesting

structure in data, where structure designates Patterns,statistical or predictive models of the data, andrelationships among parts of the data (Fayyad &Uthurusamy, 2002) [4,5] . We used different algorithms toextract the valuable data. Data mining is important tool totransform the data from large quantities of data throughusing pattern matching. Data mining has manyapplications in security including national security,terrorist activities and cyber security. However, theusefulness of this data is negligible if meaningfulinformation or Knowledge cannot be extracted from it.Data mining, otherwise known as knowledge discovery,attempts to answer this need. In contrast to standardStatistical methods, data mining techniques search forinteresting information without demanding a priorihypotheses. Finding links between data fields, Useregression to predict future values of data and Model

Intelligence Techniques for e-governmentapplications

HANAA. M. SAID 1, MOHAMED HAMDY 2, RANIA El GOHARY 3 and ABDEL-BADEEHM. SALEM 4

1 Faculty of Computing & Information Science Ain Shams University, Abbassia, Cairo, EGYPTE





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sequential patterns in the data that may indicate revealingtrends (Tam and Kiang, 1992; Chu & Widjaja, 1994) [6].Cyber security involves protecting information by preventing, detecting, and responding to attacks. Cybersecurity also referred to as information technology

security, whose main focus is protection of computers,networks, programs and data from unauthorized access,change or destruction. The real cyberspace that isavailable on the internet. It is very difficult, to conduct onthem the assessment of quality. That can be accepted forthe extent of securing it. It can be expressed for this realcyberspace as if the series of the minor cyberspaces. Theimportance of inferring process of the reference measurein the form of procedural assessment is to improve theknowledge and helping in the decision making for the e-government services. A series of the standards are builton the application of data mining methods specificallyrepresented as "Frequencies", "decision tress model","Logistic regression", "association rules model", " Neural Networks Model", "Hierarchical Clustering" and'Bayesian network' for making reference measurements, tomeasure the extent of securing the data, and the providedservices.A penetration test is an in-depth information risk analysis practiced to assess the security of the systems from ahacker’s perspective. Penetration Testing and WebApplication testing service simulate a hacker or anattacker like environment to conduct the exercise so as tomatch the hacker’s thought process. Penetration testingcan be done by both the Internet and local area network

depending on the placement and operational usage of thesystem such as: Web Application Penetration Test(Application discovery, Data Mining, Cryptography,Database Listener and Business Logic Testing) [13].For the above mentioned reasons, we formed intelligentapproach for securing the data that consists of penetrationtest that includes (DM-ID), the results of intelligentapproach and penetration testing are used to find outsecurity defects and to patch them before it will be toolate. This brings testers to adopt automatic tools widely, asit is demonstrated by the continuous release of platformsfinalized to automate this process, discovering gaps in

compliance, finding defects now before somebody elsedoes, verifying secure configurations, testing newtechnology and reporting problems to management.Collaborative processes oriented on large data sets are presented [14].Also, we will compare the effectiveness of various types oftechniques and algorithms of different technologiesresearches. These help in choosing between severalalternatives take of decision making. This paper impartsnumbers of applications for the data miningmethodologies in cyber security. It have been developedand deployed to protect computer systems against networkattacks, we discuss various types of variety of techniques,approaches and different areas of data mining techniquemodels in cyber security from "different perspectives E-government", describing how data mining helps indetection and prevention of these attacks. Finally Results

applied on the site of "Cairo Cleaning and BeautificationAgency" governorate in Egypt www.ccba.gov.eg; it is oneof the important cyberspaces in the frame of themechanism for the e-government services, and its effecton both the citizens, the investors and on the government,

this cyberspace is related with several electronic sites.Combinations of different intelligent system approaches toform hybrid intelligent systems continue to find newapplications. Security must be addressed in the phase of planning and designing of E- government System,Management process is needed to assess security control,where management allows departments and agencies tomaintain and measure the extent of data securitydepending on the mechanism of revealing the securityweak points .Revealing the weak points is done by using aseries of standards built on the application of machinelearning methods specifically Using the Neural NetworksModel, and intelligent data analysis. All these techniquesare useful in monitoring and measuring the extent of thesecured data and the provided services.The fuzzy set theory was introduced by Zadeh [25]. Fuzzylogic is a multi-value logic which permits intermediatevalues to be defined between conventional ones liketrue/false, low/high, good/bad etc. In a classical set theory,an element may either belong to set or not. In fuzzy settheory, an element has a degree of membership. A degreeof membership function can be described as an interval [0,1].This paper introduces Intelligent Approaches for Securingthe Data, these approaches are based on intrusion

detection, analysis and monitoring, in order to form penetration test that helps decision makers to take theright decision for facing the threats and control systemoperations.The strategies of " Frequencies", "decision tress model","Logistic regression", "association rules model", " Neural Networks Model", "Hierarchical Clustering" and'Bayesian network" will be utilized in forming datamining intrusion detector (DM-ID), this in turn will beused in forming penetration test that will monitor,measure and test of the audit data and events. Taking intoaccount that, each module will work independently to

detect intrusions in the network traffic data.This paper may be useful tool that enables thegovernorate to find the major points for managing theeffective government services , type of the data to beused , type of data that has been moved in a proper way ,what are the terms or the requirements that are used inthe data organizing , arranging the knowledge from theview of the priority and importance performance fordiscovering them , compiling the processes based on thefollowed standards.This paper consists of 4 sections; the first section is theintroduction as we are able to get huge information aboutthe literature survey. For assessing the security of thecyberspace, the second section Comparative IntelligentTechnique Approaches for E-government Security ofsecuring the data when introducing the strategicinformation for the different rendered services through the


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minor cyber service. Moreover the concentrates on themeans of research and measurements that are used andsuggested and how to use them are presented in thesection 3.Also presenting the discussions about thedifferent results, finally in section 4 we summarized and

concluded the future work.2. R ELATED WORKData mining techniques have been successfully applied tovarious private sector industries in marketing, financialservices, and health care. Governments are using datamining for improving service delivery, analyzingscientific information, managing human resources,detecting fraud, and detecting criminal and terroristactivities. However, literature is scarce regarding theapplication of data mining to a project orientedenvironment. Generally, the purpose of this paper is toshow how data mining concepts may be applied in a

project oriented environment. It will examine the so called project success framework and show how data miningmay be utilized at particular stages to increase the chancesof delivering successful projects that will have theintended impact on the corporate business strategies of private and public sector organizations.data mining has evolved in a wide variety of directions,ranging from complexity control of algorithms to thedevelopment of applications for many domains, such ascounter terrorism, medical diagnosing, marketing and soon (Antonie, Zaïane & Coman, 2001; Bach, 2003; Bank,Min Tjoa & Stolba, 2006; Bhattacharyya, 1999; Choenni,2000; Wang & Han, 2000). The extraction of econometricmodels, however, has received relatively little attention inthe field of data mining.An econometric model is a model that specifies thestatistical relationship that is believed to hold between itsvariables. These models play a central role in many fieldsof research and become increasingly important inforecasting tools. For example, in finance, stock pricesmay be expressed in terms of other stock prices andmacro-economic variables, such as industrial productionand interest rates (Cheung & Ng, 1998; Nasseh & Strauss,2000; Pesaran & Timmermann, 2000). Another example,within government forecasting, is the modelling of

recorded crime, which may be expressed in terms ofdemographic and macro-economic variables, such as thenumber of young males and unemployment (Deadman,2003; Greenberg, 2001; Hale & Sabbagh, 1991). Twocommon econometric models are the linear regressionmodel and the cointegrated model.Cyber security is not a single problem in e-government, but rather it is a group of highly different problemsinvolving different sets of threats. Fuzzy Rule basedsystem for cyber security is a system that consists of a ruledepository and a mechanism for accessing and runningthe rules. The depository is usually constructed with acollection of related rule sets. The aim of this study is todevelop a fuzzy rule based technical indicator for cybersecurity with the use of an expert system which is namedFRBCES (Fuzzy Rule Based Cyber Expert System). Rule based systems employ fuzzy rule to automate complex

processes. Common cyber threats assumed for cyberexperts are used as linguistic variables in this paper.We persistent computer security vulnerabilities mayexpose the government’s critical infrastructure andgovernment’s network systems to cyber attack by

terrorists, possibly affecting the economy or other areas ofthe national security at large [12]. Furnel and Warren [13]discussed the problems posed by cyber terrorists. Theyconsidered the nature of the responses necessary to protectthe future security of society. By the rising threat of cyberattacks, some researchers tried to describe cyber threat andmade attempts for finding a solution to their studies [14]-[17] this show in figer1.So far, many studies have been done on cyber security, butthese are mostly focused on prevention of cyber intrusion,[18]-[21], effects of cyber attacks or on different machinelearning applications [5],[6],[8]-[10]. Although there aresome studies using fuzzy rules [22]-[24], fuzzy expertsystems’ effectiveness are totally different analysis. In this paper, apart existing literature, a new approach has beendeveloped to prevent cyber attacks using a fuzzy expertsystem. The proposed fuzzy expert system in this studygives valuable information to system administrators toimprove the achievement of the cyber security. This workcontributes to the system in a general manner and it can be adapted to different cyber security scenarios.

Figer1: E -government application

Table 1 Distribution of articles according to datamining and its applications of e-government


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Hong Yu et al. [17] performed comparative study on datamining for individual credit risk evaluation. Theresearcher found that credit risk is referred to as the riskof loss when a debtor does not fulfil his debt contract andit is of natural interest with respect to practitioners in

banks as well as to organizers.Ji Dan et al. [18] performed synthesized data miningalgorithm based on clustering and decision tree. At present, they have accumulated abundant agricultureinformation data for the vast territory and diversity of cropresources. However, we just can visit a small quantity ofdata for lack of useful tools.Mohamed El far et al . [19] compared between datamining algorithms: "Close+, Apriori and CHARM" and“K-means classification algorithm” and applying them on3D object indexing. Three-dimensional models are moreand more used in applications in which the necessity tovisualize realistic objects is felt (CAD/CAO, medicalsimulations, games, virtual reality etc.).Wangjie Sun et al. [20] implemented an advanced designof data mining algorithms. In order to save the computerdata effectively, we should not only check the integrity forthe data, but also we have to check storage system torecover data in a timely manner to reduce losses to aminimum, to prevent the recover fails when the faultoccurred. S.P.Latha [20] presents algorithm for efficientdata mining. Over the years, a variety of algorithms forfinding frequent item sets in very large transactiondatabases have been developed. Data mining algorithmsare used extensively to analyze business, commerce,scientific, engineering, and security data and dramaticallyimprove the effectiveness of applications in areas such asmarketing, predictive modeling, life sciences, informationretrieval, and engineering.In April 2007, Estonia suffered a major cyber-attack,after which Estonia contributed in securing cyber spaceworldwide. According to Joak AAVIKSOO, Minister ofeducation and Research of Estonia, they analyzed weak points in their infrastructure [58]. As per their conclusionstheir law enforcements, border line do not hold incyberspace [58], most of the infrastructure is not undersingle body and 80% of web infrastructure is in private

hands [58].In 2008, Estonia formulated a National Cyber SecurityStrategy. The objective of National Cyber SecurityStrategy is to ensure cyber security and help privatesectors to develop highly secured standards [21]. InMalaysian primary schools, cyber bullying and hackingare the major occurring crimes [66]. There is an AdaptiveInformation Security Model that was developed to lessenthe gap between what we can do and control ICT [36].There are five critical systems that ensure the highlysecured and prospered network [36]. Forty-one41 internetcrimes have been analyzed [36]. The analyses show thatvictims were missing in these five security tests [36].A penetration test on internet service provider wasconducted in Sweden [37]. In Burma just before country’sfirst national elections in twenty years, the internet wasshutdown [31]. Offenders usually use public places to

commit crimes which hides their identity and where thereis no effective legislation. Internet gave birth to terrorist propaganda. Radicalization can be done using internet.MIS configuration of websites causes search engines to penetrate into website and causes illegal access to data

[66]. Search engines need to obey some rules to disallow,some folders, files and images [66].Halfond et al [23], [24] presented a technique for penetration testing, which involves static and dynamicanalysis to increase the efficiency of the informationgathering and response analysis phase. The authorimplemented static and dynamic analysis to improve penetration testing. To discover the input vector, the staticanalysis technique of automatic response that analyzes thedynamic analysis technique is used. The main objective ofdynamic analysis is to find error while running the program. To test the effectiveness of these techniques, anexperiment was conducted for static and dynamic analysis based penetration testing on nine web applications [23].Halfond et al [24], developed Amnesia (Analysis forMonitoring and Neutralizing SQL Injection Attack). Theauthors proposed a model based technique that combinesthe static and dynamic analyses. In this paper the tool firstidentifies hotspot, where SQL queries are issued todatabase engines. Non-deterministic finite automata areused at each hot spot to develop query model (2009).Xiong et al [9], [10 ] presented an approach of modeldriven framework that integrates the softwaredevelopment life cycle phases with penetration testing process, so vulnerability can be easily detected and testingcan be done repeatedly by the expert personnel, to test thecost effectiveness, systematic and fully integrated intosystematic and fully integrated into a security orientedsoftware development life cycle, security experts are stillrequired to maintain knowledge. The test cases arederived from models.Stepien et al [6] presented an approach to penetrationtesting inherent to penetration testing of web application,the approach consists of TTCN-3 languages inherentfeatures. Also, it derives the functional test cases and hastaken an example of a malicious bank website. This paperdescribed a message sequence diagram of a malicious

bank website to show the XSS attacks. It generates thefunctional test cases.Pietraszek et al [26],[27] presented an approach of Taint based technique in which the authors modified PHPinterpreter to track taint information at the character level,context sensitive analysis is used in this technique to rejectSQL queries if an entrusted input has been used to createcertain types of SQL tokens. The advantages of thisapproach are that they require modifications to the runtime environment, which decreases the portability.Arkin, Stender and McGraw (Arkin, B. et al 2005)[28] investigated the importance of the subject from thesoftware pen-testers perspective, concentrating on wherethe role of the tester lies when flaws are assessed duringsoftware development. Within the software developmentlife cycle, Arkin et al. suggest without proper and timelyAssessment, organizations “...often find that their


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software suffers from systemic faults both at the designand implementation levels” (Arkin, B. et al, 2005). Thesame can be said for the network security of organization;without proper and rigorous assessment, the networkdesign of an organization will lead to unknown flaws

inherent in the network implementation. The same can besaid for the network security of organization.Pierce, Jones and Warren (Pierce, J. et al, 2007) [29] intheir paper provided a conceptual model and taxonomy for penetration testing and professional ethics. They describedhow integrity of the professional pen tester may beachieved by “...avoiding conflicts of interest, the provisionof false positives and false negatives and finally do thelegally binding testers of their ethical obligations in [their]contract” This is certainly noteworthy and should beexpected of an individual working with potentiallysensitive information; however, this appears more of a personal “ethical code of conduct” than something thatcan be enforced and assessed. Pierce et al (Pierce, J. et al,2007) also discussed the provision by universities“...toward offering security testing courses”.McRue ( McRue, A., 2006) , [30] Commented on the"first U.K. University to offer a dedicated degree course inhacking "This has certainly shown an emerging trend inthe educational sector for penetration testing courses;however these tend to be degree classifications and notnecessarily an industry recognized Certification standard.The literature review shows that data mining is keyingredient in the solution to information security problems. The author in [31] discusses the development ofdata mining and its application areas. Soft computingframework data mining is presented in paper [32] wheresoft computing approaches like fuzzy logic, neuralnetwork are discussed. Data mining provides a number ofalgorithms that can help detect and avoid security attacks[33].The author in [34] presents a survey on various datamining techniques for intrusion detection wherein thetypes of intrusion attacks like network and host based arealso summarized. One of the intrusion detectiontechniques known as anomaly detection has beendiscussed in details [35]. Paper [36] specifies themeasurement criteria for intrusion detection. Fraud

detection is another area of focus as the number of onlinetransactions is rising exponentially. Various types offrauds like computer fraud are given in [37] with therespective techniques to overcome the situation. A numberof methods are proposed for privacy preserving throughdata mining in [38], for example K-Anonymity. In paper[39], author talks about the sensitivity of data which mayrisk an individual’s privacy. This data can be general data,user specific or authentication data. Peter in [40] specifiesaspects of cloud computing and the top cloud computingcompanies with their respective key features. The cloudsecurity issues have been addressed via a trusted third party in [41]. Data mining techniques can also be used forthe analysis of various firewall policy rules [42]. Securityframework for mobile cloud computing is proposed in[43]. In [44], the authors have identified the followingtypes of attacks which are major threats to cloud

implementation denial of service attack, Cross virtualmachine side-channel attack, malicious insiders’ attack,Attacks targeting shared memory, and Phishing attack.Table 1 briefs the review of variety of work done in thearea of cloud computing security with the help of data

mining techniques. Paper [15] details the need of mobilecloud computing. As the mobiles are getting cheaper withthe availability of internet facility, a mobile can also beconsidered as an entity in a cloud.Malicious insiders’ attack, Attacks targeting sharedmemory, and Phishing attack. Table 1 briefs the review ofvariety of work done in the area cloud computing securitywith the help of data mining techniques. Paper [15] detailsthe need of E-governments cloud computing. The E-governments are getting with the availability of internetfacility, the E-governments can also be considered as anentity in a cloud.Currently, many data mining and knowledge discoveryframeworks and data classification for everyone anddifferent usage such as the Real-time (On line)Environment for Knowledge Analysis RTDMM [1] , otherXiong Deng et al, AKDT [9], other Olivier Thonnard et al, DMCS [10] , other Bhavani M.Thuraisingham, APSO[11], other Sandeep Rana et al, SCDI [12], otherChandola DI et al ,ITICS [13]] , other KutomaWakunuma ET AL , GPLCA [14] , Other Ap Jian Zhang1ET etc[55].These Frameworks provide a set of methods andalgorithms that help in better utilization of available dataand information to users; including methods and

algorithms for data analysis, cluster analysis, geneticalgorithms, nearest neighbor, data visualization,regression analysis, Decision trees, Predictive analysis,text mining, cyber security, world wide web , semanticweb Data mining argent, and amplification approach etc.Intrusion detection (ID) is the process of monitoring andanalyzing the data and events occurring in a computerand/or network system in order to detect attacks,vulnerabilities and other security problems, Figure 2 below shows a traditional framework in governmentdecision making, for improving the efficiency of servicedelivery. [15].

Figure 2: traditional framework for ID3. Proposals From above mentioned studies and according to theseveral advantages of (DM approaches and "Penetrationtesting") for E-government intrusion detection, we suggestthat a combination of both approaches can help indeveloping a new generation of high performance IDS. Incomparison to traditional IDS (Fig.3), IDS based on DM


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and "Penetration testing" is generally more precise andrequires far less manual processing and input from humanexperts.In this paper we used the application of Minor cyber“Cairo Cleaning and Beautification Agency”

(www.ccba.gove.eg) in Egypt. The following describes ourapplications of different techniques in the minor cyberspace's which is the cyberspace for the authority ofcleaning and beautifying Cairo, in the Arab Republic ofEgypt (www.ccba.gov.eg) to Analysis the extent of thesufficiency for the suggested reasoning to measure theextent of securing data for the cyberspace.We formed "intelligent approach" for securing the datathat consists of penetration test that includes ("MiningAudit Data for Automated Models for Intrusion Detection"(MADAM ID); for evaluating the security state of asystem or network by simulating an attack from amalicious source. This process involves identification andexploitation of vulnerabilities in real world scenario whichmay exist in the systems due to improper configuration,known or unknown weaknesses in hardware or softwaresystems, operational weaknesses or loopholes in deployedsafeguards.We will use strategy of inferring and analyzing the data,searching for them in the cyberspace by one of thetechnology tools (data mining), through the cyberspace,enabling fighting terrorism to limit the harms inadvance by making the relief arrangements from theview of comprehensive security and through the analysisof the results for the data survey as it depends on using

the models of test to assess the extent of the correctnessand safety of the data identifying the standards of testthat can exceed the limitations of the available data ,such as using the proposed model in the Figure 3"To test the extent of the data correctness for thecyberspace, and that the infrastructure of the proppedmodel of cyberspace for "the Cairo Cleaning andBeautification Agency", a model will be built in stepsrepresented in 2 states as follows:• The first stage ("Frequencies", "Association rules","decision trees" and "hybrid of auto regression") [20],[72], [73].

• The second (" Neural Networks Model"," HierarchicalClustering" and 'Bayesian network") to enable thedecision maker to know interact with the features of thevalue traits. And the data extraction tools will be adaptedwith data mining [74], [75], and [76].Penetration testing was among the first activities performed when security concerns were raised many yearsago [3]. The basic process used in penetration testing issimple: attempt to compromise the security of themechanism undergoing the test. In earlier years, computernetworked operating systems, with their access controlmechanism, were the most suitable components for penetration testing, because O.S. is the core component ofthe machine, so it is more exposed to security threats [3].The earliest penetration testing processes were highly andmanually intensive, while later automatic processes startedto be clearly utilized for cost reduction [3].We need to

determine how the attacker is most likely to go aboutattacking a network or an application. Locating areas ofweakness in network or application defenses, determineshow an attacker could exploit weaknesses, Locatingresources that could be accessed, altered, or destroyed,

determine whether the attack was detected, determinewhat the attack footprint looks like and makingrecommendations.Other benefits of feature selection are: improving the prediction of ID models, providing faster and cost-effective ID models, providing better understanding andvirtualization of the generated intrusions.

Figure 3: The proposed IDS model based on DM and penetration testing

Figure 3 shows the proposed "IDS "model based on "DM"and "penetration test ". The system is composed of thefollowing units:

Computer network sensors: collect audit data andnetwork traffic events and transmit these data to IDunits.

DM-ID unit : contains different modules that employvarious DM algorithms and techniques (e.g.,

Frequencies, decision tree model, logistic regressionalgorithms, neural networks model, Bayesian networkmodel etc.). Each module works independently todetect intrusions in the network traffic data.

Penetration test unit : deploys penetration test todetect intrusions in the network audit data.

Collect detected intrusions unit : collects detectedintrusions from DM and penetration testing units.

Virtualization unit : help monitor and visualize theresults of penetration test units.

Managerial decision maker : analyzes intrusionresults, evaluates system performance, takes decisions

on detected intrusions, checks for negatives and positive results, controls system operation, generates a performance report and decides if anychanges/updates are needed.


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(Analysis of the results)Finally we can find that the cyberspace needs to beimproved, its efficiency needs to be enhanced andnecessary arrangements should be taken to raise theefficiency of security. As the data is exposed to violations

at the rate of 92,308 we can find that were achieved byhigh rate (timeliness= 94 % & integrity = 92.3 %&objectivity = 91.7 % & availability=% 96), we find thatthe feedback value was achieved at the medium rate.Table 4: Report of the proposed procedure modelingWe conclude that the maximum number of the frequenciesidentified to set the accuracy of data is less probability(verifiability) for occurrence 0.309. It's clear in table 4.(Refer to Hanaa. M et al., 2012),[20],[72],[73],[74],[75].

Table 4: Report of the proposed procedure modeling

4. EvaluationTo improve the framework, we have to take intoconsideration the previous challenges, many of thesechallenges cannot be solved by technology alone, but theyrequire understanding the collective social dynamics asroots of problems and key to their solutions.The basic difference between the current study and the previously mentioned studies can be summarized in thatthe current study is applied on certain minor cyber inEgypt, "Cairo Cleaning and Beautification Agency".Another difference is represented in "penetration testmodel" as a collective approach that gathered all strategies(Frequencies, Association rules, decision trees, hybrid ofauto regression, Bayesian network and Neural NetworksModel). The previous studies used one of these strategies but there is no study that used two strategies together.This make the current study different in its methodologyfor treating with security of data.

However, the above mentioned table (4) which shows theoutputs of the previous function of assessment was ofseveral values. Each case can be diagnosed correctlyaccording to the standardized shape. However, in practice,it was not preferred to see100% accuracy, but you can use

the assistant analysis in identification if the model ofaccurate and acceptable application of the cyberspaceactually, or that there is no other type of function or ofsins nor linear that can apply , however with the set ofdifferent data , it is possible for the results to be easilydifferent. Thus, it is always worthy of trial, with full set ofchoice.

From all the above mentioned we found thefollowing facts:

• Data mining predict assist in: Identifying patterns ofcriminal or terrorist behavior, Identifying emergingcriminal or terror threats, predicting future criminalor terrorist actions, Prioritizing intelligence andexploiting criminal/ terror threat vulnerabilitiesPenetration test necessary for E-government.

• Penetration test also can be used as an important anduseful indicator in security measurement. E-government needs to new technology in order to beable to follow the new challenges that may face thecyberspace, in addition to identification of securitythreats. Finally there are many reasons that makecyberspace needs for penetration test, thesereasons can be summarized as follows:

Determination of the effectiveness of the security controls

and adjusting their appropriate locations, determinationthe points of weakness and strength in cyberspace securitysystem, determination of the sufficiency of the currentcontrols in cyberspace security system and determinationof the threats against the organization's information;We believe that the development of such a framework ismainly an exercise of measurement, simply because inorder to evaluate, compare, predict and control effectively,measurements are required. Thus our current researchefforts concentrate on the development of an “e-Government security system”, able to face the challengesthat confront e-Government software project.

Data mining involves the use of sophisticated dataanalysis tools to discover previously unknown, valid patterns and relationships in large data sets. Data miningconsists of more than collecting and managing data; italso includes analysis and prediction. The application of patterns, relationships, and rules to searches, whetherthese are derived through data mining, observation,intelligence, or theoretical models.The security of information in computer-basedsystems and networks continues to be a majorconcern to researchers. The work in intrusiondetection techniques and methodologies which has been a major focus of information security-relatedresearch in the past two decades is certain tocontinue. The area of intrusion detection iscontinuing to evolve. While a number ofmethodologies and tools have been designed to assist


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in the identification of intruders, no definablestandard has been developed which could serve asthe basis for a deployable intrusion detection tool.However, as the processing capabilities of computersystems improve and the innovative approaches to

intrusion detection continue to be developed, thecreation of an effective intrusion detection standardis inevitable.5. Conclusions This paper has been conducted a comparison betweendifferent data mining frameworks as Penetration test forclassification purposes, it presented an overview of thetechniques that had been utilized for the detection ofattacks against computer systems, and a survey of theexperiences of those most affected by intrusion detectiontechnology.This paper provides the review of literature on how data

mining techniques and related algorithms can play a vitalrole in ensuring information security in an E-government.We have also reviewed some of the significant techniqueswhich hold the promise of effectively protecting computersystems. It is obvious that our national security apparatusis driven by a reactive focus on the crime or terrorincidents. However, the crime incidents or terror attacksare merely the end products of a complex set of criminalor terror activities.Also, it shows general vision for how to utilize intelligentapproaches for securing the data in E-governmentinformation systems through measuring the extent ofsecuring the extraction of the required data on electronicsite, and becoming able to fight the cyber terrorism, as wedepended on using a set of models to measure the extentof the correctness and security of the data.The data mining of data security data (e.g., related to police operations) could enable the discovery of systemicinefficiency in connection to security response, crimeincidence analysis and prevention efforts. Data miningcould help provide explanation of crime and terror. Thedata mining techniques however could mine the historicaldata and extract hidden predictive information whichcould prove the initial assumption that it will facenumerous problems.

However data mining can be a valuable tool in the handsof the decision makers aiming to predict the internal andexternal environment, adjust accordingly and hence tomake more rational decisions.Also included are ways to achieve sustainability for thiscritical E– governance project and so safeguard ournational critical data from digital terror and fraud. This paper initiates concepts relating to the establishment of aneffective framework for data management of digitalevidence. The current intelligent approach is very usefultechnique for building strategies that measure the extentof securing data in order to improve the management performance, through the filtration of data. Also thesuggested technique could become an important tool forthe government and intelligence agencies in the decision-making and monitoring potential international terroristthreats.

In the future we will complete and follow up the researchin this field through using search in data to be an activeway in decision making. It is expected that there will beseveral challenges related to operation and development ofcyberspace system. In future also the penetration test can

be an effective tool that will help in testing the security ofthe data, especially if it is developed according to dynamicand automated aspects. Many future directions can beexplored in this still young field. For example, more visualand intuitive criminal and intelligence investigationtechniques can be developed for crime pattern andnetwork visualization.Finally the resulting system can become an important toolfor government and intelligence agencies in decisionmaking and monitoring of real-time potentialinternational terror threats present in blog conversationsand the blogosphere.

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[71] Hanaa. M. Said, Mohamed Hamdy, Rania El Goharyand Abdel-Badeeh M. Salem ‘‘Cyber space security

assessment Case study ’’ book paper IGI Global for publication in the book,"Threat Detection andCountermeasures in Network Security" 701 E.Chocolate Avenue, Suite 200. Hershey PA 17033-1240, USA -2013. http://www.IGI-Global.comRelease Date: October, 2014. Copyright © 2015. 347, pp. http://www.igi-global.com/book/threat-detection-countermeasures-network-security/110015.

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[74] Hanaa. M. Said, Mohamed Hamdy, Rania El Goharyand Abdel-Badeeh M. Salem "NEURAL NETWORKS APPROACH FOR MONITORINGAND SECURING THE E-GOVERNMENT

INFORMATION SYSTEMS" European Journal ofComputer Science and Information TechnologyVol.2, No.4, December , Published by EuropeanCentre for Research Training and Development UK(www.eajournals.org), pp. 29-39, 2014.

[75] Hanaa. M. Said, Mohamed Hamdy, Rania El Goharyand Abdel-Badeeh M. Salem "Hierarchical ClusteringApproach For Monitoring and Securing the Data inE-Government Systems" International Journal ofEmerging Trends & Technology in Computer ScienceISSN 2278-6856 (IJETTCS, http://www.ijettcs.org)Id: IJETTCS-2014-12-01-74, Volume 3, Issue 6,

Impact Factor 3.258 [ ISRAJIF], pp. 085-091, 2014.AUTHOR

Hanaa Mohamed Said is generalmanger OF Information &Computer Center at Cairo Cleaning& Beautification Authorized,Egypt. Eng Hanaa Mohamed Saidis responsible for Supervision of all

administration tasks for five departments as follows: TheCenter of information, Eng Hanaa Mohamed Said gotB.SC. in communications Engineering, Faculty ofEngineering, Helwan University, Graduation 1987, Dept :Telecommunications & Electronic, Project: Design ofMicroprocessor, Eng Hanaa Mohamed Said got a diplomaof computer science from Ain Shams university with verygood , Eng Hanaa Mohamed Said got a Master degree of


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Volume 4 Issue 2 March – April 2015 Page 20

science in Information Systems college of computing &information Technology In jolly 2011 Grade: "Excellent"From Arab Academy For Science, Technology &Maritime Transport Eng Hanaa Mohamed Said on herway to take PHD from Faculty of computer science at Ain

Shames University Faculty of Computing & InformationScience Information Systems Department .

Dr.Rania Elgohary is anassistance professor at the Facultyof Computer and InformationSciences, Ain Shams University,Cairo, Egypt. Rania Elgohary gotB.SC. in Accounting and ForeignTrade, Faculty of Commerce and

Business Administration, Helwan University, Cairo,Egypt, also B.SC complementary in computer sciencefrom Faculty of Computer and Information Sciences, AinShams University, Cairo, Egypt, and Rania Elgohary got aMasters degree from Ain Shams University, Egypt incomputer and information sciences, Information SystemsDepartment, on Titled: “Deliberation Process Mechanismsfor Software Development”. Dr Rania got a PhD degreefrom University of Ain Shams, Cairo, Egypt. Dr. RaniaElgohary is known and well recognized authority in thedomain of Development and the applications of softwareengineering. Her research interests include softwareengineering, E-Business, stock Market Exchange,surveillance systems and information security.

Dr. Mohamed hamdy is assistantProfessor with more than 14 yearsexperience years in both Researchand Teaching in many fields ofComputer Networks and ComputerScience in general. He gets this

experience in leading universities in MENA and Europe.BSc and MSc degrees in Computer Science at Ain ShamsUniversity in Egypt formed a solid background and a setof Research and Teaching skills. During my PhD at theUniversity of Jena in Germany, and for about five years,he has conducted a set of highly ranked and reputed

research groups in several occasions.He acquired highmanagerial skills as working on the top IT strategicmanagement at Ain Shams University as director for alarge enterprise network like Ain Shams University Network. He managed to provide several strategic visionand solutions for many challenges in this job.

Prof. Dr. Abdel-Badeeh MSalem He is a Professor ofComputer Science since 1989 atFaculty of Computer andInformation Sciences, Ain ShamsUniversity, Cairo, Egypt. He is a

professor emeritus since October 2007. He was a Directorof Scientific Computing Center at Ain Shams University(1984-1990). His research includes intelligent computing,expert systems, biomedical informatics, and intelligent e-

learning technologies. He has published around 300 papers in refereed journals and conference proceedings inthese areas. He has been involved in more than 300conferences and workshops as a plenary speaker, memberof International Program Committees, workshop/invited

session organizer and Session Chair. He is author and co-author of 15 Books in English and Arabic Languages. Heis the Editor-in-Chief of the International Journal of Bio-Medical Informatics and e-Health (IJBMIeH), EgyptianComputer Science Journal (ECSJ), Associate Editor ofInternational Journal of Applications of Fuzzy Sets andArtificial Intelligence (IJAFSAI).

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