A hierarchical algorithm for cyberspace situational awareness based on analytic hierarchy process
- 期刊名字:高技术通讯(英文版)
- 文件大小:112kb
- 论文作者:Hu Wei,Li Jianhua,Jiang Xingha
- 作者单位:Department of Electronic Engineering
- 更新时间:2020-11-22
- 下载次数:次
294HICH TECHNOLOGY LETTERSIVol. 13 No.3ISept. 2007son matrix between hosts and network can be obtained asThe results are shown as follows:the followingλmax = 8.0233W =[0.1919,0.1919 ,0.0575,0.0575 ,0. 1031,H「15210.1031 ,0.1031 ,0. 1919]T.1/5 1 1/2According to the Eqs. (5) and (6), the unifomityjudgment is shown as the following:By nommalizing each column vector in pairwise com-8.0233一8= 0.00338-1parison matrix of the host-network, the eigenvector W =0.0033[0. 5954,0.1283,0.2763]T and maximum eigenvalueCR=R=1.40= 0.0024 << 0.1.λmx = 3.0055 are obtained. Here, the number of hosts is(2 )The judgment matrix of the services provided by3. Based on the historical research on AHP, the index ofRandom Identity ( RI) is 0.58. Hence,cI=Amex-n.=3.0055-= 0.0028H2→S=lI3- 1The computation results are as follows:CR =CI 0. 0028the maximum eigenvalue λmax = 2,RI=0.58=0.0047<<0.1The above computations show that the inconsistencythe eigenvector W = [0.6667,0.3333]T, CI =0index of the judgment matrix is acceptable. Then,and CR=0.0.5954, 0. 1283 and 0. 2763 are the importance weights(3)The judgment matrix of the services provided byof the hosts H;, H2 and Hz, respectively.Following the above procedure, the judgment matrixof each host is also constructed, and the eigenvector andeigenvalue are calculated, The uniformity judgment is giv-H3+S=1/31/311en below.(1)The judgment matrix of the services provided byThe maximum eigenvalue λmux = 4; The eigenvectorW = [0.375,0.375,0.125,0.125]", CI=0 and CR =Hl→S=0. The results show that the constructed matrix satisfiesthe condition. Finally, the total importance rank of each33service provided in the network is shown in Table 2.1/31/3111/21/21/21/3The uniformity check of the general rank of weightingcoefficients is described in detail as the following1 1/2CI=2H;.CI;=0.5954x0.0033+0.1283x1/21/2221/20+ 0.2763 x 011331.= 0.002:able 2 The weighting coefficients rank of the services and hostsHost levelHost HHost H2Host H3General rankService level0. 59540.12830.2763RPC0. 19190.66670.3750.3034WEB00.1143SOCKS0.05750.1250.0688PROXYSNMP0. 10310.0614FTP0.33330.1041NetBIOSTELNET).1919DNSC0. 1036中国煤化工CN MHG .296HIGH TECHNOLOGY LETTERSIVol. 13 No.3ISept. 2007National Symposium on Sensor and Data Fusion, 1999. 1-63 Conclusions[ 5] XiaoHD, Li J H. Analyeis of security aituation of networksbased on knowledge base. WSEAS Trans on Electronics ,2006, 3(1): 34-39It is an emenging technique to utilize multi-source[ 6] ChenXZ, ZhengQ H, Guan X H, et al. Approach to secu-data with weighting cofficients to achieve a quantitativerity evaluation based on rough set theory for host comnputer.description about the overall data. By combining the alertJournal of Xi' an JiaoTong Unizersity , 2004, 38(12): 1228-necords and fusing the data from the bottom to the top,1231, 1255 (in Chineae)the quantitative evaluation of the attack degree that the[ 7] Li W s, Wang B S. Sitnation asment based on Bayesiannetwork suffers can be accomplished. The above proce-network. Systems Engineering and Electronics , 2003, 25(4):dure will be the goal of the network management systems480- 483 ( in Chinese)in the future. Starting with the Snort alerts, this paper[ 8] Mahew S, Shah C, Upadhyaya S. An alert fusion frameworksituation awareness of coordinated multistage attacks. Inimplements a great deal of calculation, and achieves theProceedings of the 3rd EEE Intermational Workshop on Infor-curent situation of the network security . The experimen-mation Assurance, Maryland, 2005. 95-104tal results reflect the security situation of the evaluated[ 9] Chen X Z, Zheng Q H, Guan X H, et al. Multiple behaviornetwork accurately, and lay an academic foundation forinformation fusion based quanhitative threat evaluation. Com-the future research. The proposed approach makes theputer & Seurity, 24 (3): 218-231analysis more reliable and easier to realize. Several mea-[10] Satty T L. The Analytic Hierarchy Process. New York: Mc-sures can be implemented to improve our proposedGraw-Hll,1980. 17-34scheme, like the order reduction of the pairwise compari-[11] Chen X Z, ZhengQ H, Guan XH, et al. Study叽evalua-tion for security situation of networked systeme. Joumal ofson matrix. It is a tradeoff between perfomance and com-Xi' an }iaoTong Unitersity, 2004, 38 (4): 404 407 (in Chi-plexity for the large scale network to meet the demands.nese)[12] The Nessus Vulnerability Scanner. http://www. nessus. com;ReferenceTenable Network SecunityTM, 2005[ 1] Hall D L, Llinas J. Introduction to mulb sensor data fusion.[13] Snort. http://www. snort. org: SourceFile Inc, 2006In: Proceedings of the IEEE Intemational Symposium on Cir-[14] Ted Hale. Analysis of Snt Alent Log for the Project HoneyNetcuits and Systeme, Monterey, 1998. 537-540Scan of the Month 17. http://www. honeynet. rg/ scans/[ 2] Bass T, Intnusion detection systems and multi-sensor data fu-scan17/ soo/ 8om1/ som1-LogAnalysis. html:HoneyNet. org, 2001sion: creating cyberspace situation awareness. Communica-[15]Nation Anti-Intnusion & Anti- Vinus Center. htp://www. a-tions of the ACM, 2000, 43(4): 99-105iav . com.cn: AI & AV, 2005 (in Chinese)[ 3] Bass T, Robichaux R. Defense -in deph revisited; qualitativerisk analysis methodology for complex network- centric opeta-Hu Wei, born in 1977. Now he is a Ph.D candi-tions. hn: Proceedings of the IEEE Military Communicationsdate in Electronic Engineering Departnent of Shanghai[ 4} Bass T. Multi-seneor data fusion for next generation distribut-Jiaotong University. His research interests include com-ed intrusion detection systems. In: Proceedings of the IRISputer cormunication network, network secunty manage-ment and data fusion ,中国煤化工CNMHG
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