文章基本信息

标题：Rule Based Classifier Models For Intrusion Detection System
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作者：Vivek kshirsagar ; Madhuri S.Joshi
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2016
卷号：7
期号：1
页码：367-370
出版社：TechScience Publications
摘要：One key feature of intrusion detection systems istheir ability to provide a view of unusual activity and issuealerts notifying administrators and/or block a suspectedconnection. Intrusion detection is a process of identifying andresponding to malicious activity targeted at computing andnetworking resources. Over the past decade, the field of IDShas been driven into overdrive by the explosive proliferation ofpersonal and server-based computers.There is need of asystematic and automated IDS development process ratherthan the pure knowledge based and engineering approacheswhich rely only on intuition and experience.This encouragesstudying some Data Mining based frameworks for IntrusionDetection. These frameworks use data mining algorithms tocompute activity patterns from system audit data and extractpredictive features from the patterns. Machine learningalgorithms are then applied to the audit records that areprocessed according to the feature definitions to generateintrusion detection rules
关键词：intrusion detection;association;rules;JRip;attacks