An Intrusion Detection Algorithm based on D-S theory and Rough Set

Abstract

Intrusion detection system is a kind of network security system which can alarm suspicious transmission or take active response measures when it real-time monitors network transmission and discovers suspicious transmission. But intrusion detection system has many problems such as wrong detection of intrusions, missed intrusions, poor real-time performance. In order to improve the performance of intrusion detection system, this paper proposes an intrusion detection algorithm based on D-S theory and Rough Set. The algorithm uses the attribute reduction algorithm in rough set to eliminate redundant attributes, form the simplest attributes set, overcome the traditional D-S theory relying on expert knowledge to provide evidence and makes each evidence body mutual independence. So it improves the evidence synthesis efficiency, shortens the evidence synthesis time and reduces the conflict phenomenon of evidence synthesis. On this basis, the paper builds an intrusion detection model based on D-S theory and rough set, and the experimental results demonstrate that the model has higher detection rate and lower false detection rate.