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《Electric Power Automation Equipment》 2006-12
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Research on intrusion detection based on SMDP reinforcement learning in electric power information network

LI Shuai1,WANG Xian-pei2,WANG Quan-de2,NIU Sheng-wei3(1.Beijing Ultra-high Voltage Corporation,Beijing 100045,China;2.Electron Information Institute,Wuhan University,Wuhan 430072,China;3.Electric Power Information Network Center of Puyang,Puyang 457001,China)  
The defense architecture and current security conditions of the electric power information network system are introduced and general defensive technologies such as the firewall and the IDS(Intrusion Detection System)are described.Defects of current intrusion detection methods are analyzed:it is difficult to determine thresholds of normality and abnormality;the false-positive rate and the false-negative rate are high.A model of intrusion detection based on the SMDP(Semi-Markov Decision Process)reinforcement learning is proposed.Its principle,algorithm and standard,as well as the Markov decision process and applications of the SMDP in the electric power information network are discussed.The improved SMDP learning algorithm lowers the false-positive rate and the false-negative rate.
【CateGory Index】: TM769
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