期刊名称：International Journal of Data Mining & Knowledge Management Process
印刷版ISSN：2231-007X
电子版ISSN：2230-9608
出版年度：2015
卷号：5
期号：3
页码：29
DOI：10.5121/ijdkp.2015.5303
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Outstanding to the promotion of the Internet and local networks, interruption occasions to computer systems are emerging. Intrusion detection systems are becoming progressively vital in retaining appropriate network safety. IDS is a software or hardware device that deals with attacks by gathering information from a numerous system and network sources, then evaluating signs of security complexities. Enterprise networked systems are unsurprisingly unprotected to the growing threats posed by hackers as well as malicious users inside to a network. IDS technology is one of the significant tools used now-a-days, to counter such threat. In this research we have proposed framework by using advance feature selection and dimensionality reduction technique we can reduce IDS data then applying Fuzzy ARTMAP classifier we can find intrusions so that we get accurate results within less time. Feature selection, as an active research area in decreasing dimensionality, eliminating unrelated data, developing learning correctness, and improving result unambiguousness.
