文章基本信息

标题：Data mining with Improved and efficient mechanism to detect the Vulnerabilities using intrusion detection system
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作者：Awan Dhawan
期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2013
卷号：2
期号：2
页码：787-791
出版社：Shri Pannalal Research Institute of Technolgy
摘要：Intrusion detection system must be capable of known and unknown vulnerabilities. We already studied the previous problems which includes detection of known vulnerabilities and unknown vulnerabilities. In order to obtain good accuracy a relevant or efficient dataset should be there to detect the known attacks and unkn own attacks. Therefore, there are numerous security systems and intrusion detection systems that address different aspects of computer security. In this research work we proposed an approach that is sequential multilevel misuse detection model with the fuzzy rules for the detection of known and unknown attacks on the efficient intrusion dataset either kdd dataset, Nsl-dataset, tcp dump etc. Empirical studies show not much performance or accuracy of detecting the known and unknown attacks. We discuss the generation of a misuse detection models from pure normal data, and also discuss the generation of sequential multilevel misuse detection models along with fuzzy rules from data that contains known classes. We apply the prop osed approaches to network-based intrusions. And the simulation of results is implemented on the good platform.
关键词：fuzzy rule; data mining; intrusion detection; multilevel misuse detection model