Performance analysis Toolset for wireless intrusion detection systems

Abstract

This paper presents a Toolset that can be used to evaluate the performance and effectiveness of wireless intrusion detection techniques. Recently, autonomic computing methods have been widely used for intrusion detection. Although some wireless intrusion detection systems (WIDSs) exist on the market, recent studies show that wireless networks are still vulnerable to complex, dynamic, and knowledgeable attacks. In this paper, we review current wireless intrusion detection systems and evaluate their performance to detect a wide range of wireless network attacks. To evaluate the performance of WIDSs, we use several performance metrics to quantify the accuracy, extendibility, adaptability, scalability, overhead, and latency of the examined WIDSs. Our experimental results show that this toolset can reveal different weaknesses in the examined WIDSs.