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A FEATURE SELECTION ALGORITHM DESIGN AND ITS IMPLEMENTATION IN INTRUSION DETECTION SYSTEM
作者姓名:杨向荣  沈钧毅
作者单位:Department of Computer Science and Technology,Xi’an Jiaotong University,Department of Computer Science and Technology,Xi’an Jiaotong University Xi’an 710049,China,Xi’an 710049,China
基金项目:ThisworkwassupportedbytheNationalNaturalScienceFoundationofChina(No.60173058)
摘    要:Innetworkintrusiondetection ,on linebehav iorpatternsareestablishedaccordingtocollectedda ta ,thenintrusiondetectionrulesaregeneratedbasedonthesepatterns1 ] .Accordingtotheserules,wecandeterminewhichbehaviorisinvasion .Thecor rectdecisionreliesontheaccuratedatausedforthedetermination .Becausethedatagatheredbythecol lectorarehugeinquantityandhavemanydescrip tionfeatures,someofthemareredundantwhichwillincreasethecostofpatternsmining ,evensomearethemainsourcesofnoisewhichwillmisleadus .Selecting…


A FEATURE SELECTION ALGORITHM DESIGN AND ITS IMPLEMENTATION IN INTRUSION DETECTION SYSTEM
Abstract:Objective Present a new features selection algorithm. Methods based on rule induction and field knowledge. Results This algorithm can be applied in catching dataflow when detecting network intrusions, only the sub-dataset including discriminating features is catched. Then the time spend in following behavior patterns mining is reduced and the patterns mined are more precise. Conclusion The experiment results show that the feature subset catched by this algorithm is more informative and the dataset's quantity is reduced significantly.
Keywords:network intrusion detection  features selection  rule induction  behavior patterns mining
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