A Non-Parametric Statistical Approach for Malicious Users Detection in Cognitive Wireless Ad-Hoc Networks

In cognitive wireless ad-hoc networks the cooperative sensing achieves more accurate results than non-cooperative ones. However, it also exposes the network to attacks. In this paper an algorithm based on the non-parametric Kruskal-Wallis test is proposed to detect malicious users without having any a priori knowledge. The algorithm makes use of the existing statistical differences between the cooperative decision and the non-cooperative decisions. Once an attack of malicious users is detected, the Conover-Inman post-hoc method is used to discern between honest and malicious users.