《粒子群算法在异常检测中的应用研究》由会员分享，可在线阅读，更多相关《粒子群算法在异常检测中的应用研究（4页珍藏版）》请在金锄头文库上搜索。
1、*2011-01-07l,2011-04-21* *:81S(2010011022-2);v(XX2009022)b* * *,o,1981M3,V3,=,Z_:?EbcI|:1003-5850(2011)06-0004-030Es_Research on the Application of Particle Swarm OptimizationAlgorithm to Anomaly Detection苏晋荣(山西大学商务学院信息学院太原030031)K1主要研究了粒子群算法在异常检测中的应用, 包括PSO算法结合聚类方法、PSO结合神经网络、PSO结合支持向量机以及单一的PSO算法, 分
2、析了各种算法的性能特点, 指出了粒子群算法在异常检测中的研究方向, 对后续研究工作具有一定参考价值。1oM粒子群, 异常检测, 聚类, 神经网络, 支持向量机ms|: TP301.6DSM: AABSTRACTThispaper mainlyresearched on theapplication of theparticleswarm optimization algorithm in anomaly detection,includingthePSO algorithm combined with clusteringmethod, PSO with neuralnetworks, PSO
3、 withsupport vectormachines anda single PSO algorithm. It analyzes the advantages and disadvantages of each algorithm, and presents the development ofapplication of theparticleswarm algorithm in anomalydetection research, which is worth referring to thefutureresearch.KEYWORDSparticleswarm optimizati
4、on, anomalydetection, clustering, neuralnetworks, support vectormachine9f?Z3a3vZL,NH,ha!aZaULaq93,i/B6,P/-G,.d/a:X4;bS_d(IntrusionDetectionSystem,IDS)dSe,#H?CmiSY,?.d/$J,yN,S_/B3L55b/ZE,S_s_( Misuse Detection)s_( AnomalyDetection)b_ZE+oy,-?_X,q,PqO?bs_y+,?_8Y,q,PqO?_b.ds_ZE1d9ZEa:SVaTa!afZEa*s_#+4s_
5、1,2,+M?/?Z,s_/|v,CfL.E3aL.Ea_4#0Es_b0E(Particles Swarm Optimization,PSO)1995MEberhartKennedy45,B8?EbL.EaVE?EM1,PSOE?,i.S_dBfL.EJ.9,2004,30(8):63-64.4 Sung A H.Identify Important Features for IntrusionDetection Using Support Vector Machinesand NeuralNetworks C /IEEE Proceedings of the 2003Symposium o
6、n Applicationand theInternet,2003.5 Eberhart R, Kennedy J. A New Optimizer usingParticle Swarm TheoryC/Proceedings of 6th IntSymposium on Micro Machine and Hunman ScienceNagoya,1995.6 Shi Y H, Eberhart R C. Parameter Selection inParticleSwarm OptimizationC/Proceedings of theAnnual Conference on Evol
7、utionary Programming,1998.7 Kennedy J, Eberhart R C. Swarm Intelligence M.San Francisco: Morgan Kaufmann Publishers, 2001.8 Ayed Salman,mtiaz Ahmad,sbahAl-Madani. ParticleSwatm Optimization for Task Assignment ProblemJ. Microprocessors and Microsystems, 2002(26):363-371.9;y.EM.:S,2004.10 Hu X, Shi Y
8、, Eberhart R C. Recent Advance inParticle Swarm C /Proccedings of the 2004Congress on Evolutionary Computation Piscataway,2004.11:,3,S,.0c(S_ZEJ.9,2008,34(4):13-15.12 Anderson J P.Computer Security Threat MonitoringandSurvillanceZ. Fort Washington,USA:1980.13 DenningD E.An Intrusion-detection ModelJ
9、. IEEETransactions on SoftwareEngineering, 1987, 13(2):222-232. (下转第9页)c6c(9432)0Es_2011Mm5mV1rT1V(qnull167.08 148.16 88.14%nullnull nullK157.08 142.15 90.49%null189.16 151.66 80.17%nullnull nullK169.75 146.25 86.15%null nulli223.08 170.33 76.35%null nullinull nullK185.91 155.91 83.86%V1LVA,|null,q,
10、Pq9Bt,|nullanulli,?4Pq,Hq/,nullanullK,?v4qb_d+y,_V?s,9apP,NnullanullinullanullKZEbID1,u,.SiftELCymJ.;,2008,37(1):45-47.2,.MPSOBP#S_J.9,2008, 34(15):168-169.19,f,f.PSOE*S_dJ.9,2007,33(14):123-125.20Z,.BPSO-SVMS+4_J.9,2006,32(8):37-39.21Wl,.PSOE_NIDSJ.9,2009,25(4-3):106-107.22R,SC,i,.0EM1s+04J.9S,2008,35(2):144-146.23B!,.f0E+4J.
