期刊名称：International Journal of Advanced Computer Research
印刷版ISSN：2249-7277
电子版ISSN：2277-7970
出版年度：2014
卷号：4
期号：15
页码：560-567
出版社：Association of Computer Communication Education for National Triumph (ACCENT)
摘要：With the growth of hacking and exploiting tools and invention of new ways of intrusion, intrusion detection and prevention is becoming the major challenge in the world of network security. The increasing network traffic and data on Internet is making this task more demanding. There are various approaches being utilized in intrusion detections, but unfortunately any of the systems so far is not completely flawless. The false positive rates make it extremely hard to analyse and react to attacks. Intrusion detection systems using data mining approaches make it possible to search patterns and rules in large amount of audit data. In this paper, we represent a model to integrate association rules to intrusion detection to design and implement a network intrusion detection system. Our technique is used to generate attack rules that will detect the attacks in network audit data using anomaly detection. This shows that the modified association rules algorithm is capable of detecting network intrusions. The KDD dataset which is freely available online is used for our experimentation and results are compared. Our intrusion detection system using association rule mining is able to generate attack rules that will detect the attacks in network audit data using anomaly detection, while maintaining a low false positive rate.
关键词：Intrusion; Security; Association rule mining; Network; Data mining.
