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《Engineering Journal of Wuhan University》 2012-01
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Filtering for network forensics data on artificial immune network clustering

YANG Jun1,MA Qinsheng1,WANG Min2,LIU Yuan1(1.School of Electronic Information,Wuhan University,Wuhan 430079,China; 2.Second Department,Commanding Communications Academy,Wuhan 430010,China)  
In order to improve the overreliance on prior knowledge in the filtering for the network forensics data,a new method for filtering the network forensic data based on the artificial immune network clustering was proposed.Taking the forensic data as the antigens and the dynamic influence-zoned B-cell as the node of artificial immune network respectively,the artificial immune network was evolved in terms of the membership grade between the antigens and artificial immune network and the stimulation of the B-cell.The network forensic data were filtered according to the filter threshold.The results indicated that the algorithm could provided higher data-compression ratios in the case of the rational selection time window and filtering threshold for ensuring an expected detection rate as well as without any priori knowledge.Therefore,the proposed method has a good ability in narrowing the scope of survey data and in the efficiency of forensic analysis.
【Fund】: 高等学校博士学科点专项科研基金(编号:20040486049);; 国家高技术研究发展计划(编号:2002AA1Z1490)
【CateGory Index】: D918.2;TP393.08
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