Data mining with Improved and efficient mechanism to detect the Vulnerabilities using intrusion detection system
Journal Title: International Journal of Advanced Research in Computer Engineering & Technology(IJARCET) - Year 2013, Vol 2, Issue 2
Abstract
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 unknown 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 proposed approaches to network-based intrusions. And the simulation of results is implemented on the good platform
Authors and Affiliations
Awan Dhawan
Keywords
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- EP ID EP125818
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