An Approach to Network Misuse Detection Based on Extension Matrix and Genetic Algorithm

摘要：

With the rapid expansion of Internet in recent years, computer systems are facing increased number of security threats. And the need to protect connected systems also increases. Intrusion Detection Systems (IDSs) are the latest technology used for this purpose. Numerous soft computing based approaches have been proposed to detect computer network attacks. This paper presents an approach based on extension matrix and genetic algorithm to network misuse detection. Based on extension matrix formed on positive and negative examples,we set up the integer-programming model (IPM) for optimal rule extraction and feature subset selection. Then genetic algorithm is applied to solve 1PM and optimal rules are generated for intrusion detection. Those generated rules are then used to detect or classify network intrusions in a real-time environment. Experimental results show the achievement of high true positive rates and acceptable low false positive rates based on benchmark DARPA data sets on intrusion.

关键词： Misuse intrusion detection genetic algorithm extension matrix.

作者: Zhixian Chen Shunyi Zhang

作者单位: College of Telecommunications & Information Engineering, Nanjing University of Posts&Telecommunications, Nanjing 210003, China

会议类型: 国际会议

会议名称: Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)

会议地点: 北京

会议语种:英文

页码: 107-113

在线出版日期: 2006-07-17（万方平台首次上网日期，不代表论文的发表时间）