A method to defense against cooperative SSDF attacks in Cognitive Radio Networks

Abstract

In Cognitive Radio Networks, malicious users collaborate to make the decision about the presence of the primary transmitter and use this information for the attacks. This type of attack is more intelligent to manipulate fusion center to make the wrong decision. We propose a reputation based adaptive clustering algorithm to defense against cooperative SSDF attacks. It is verified that our algorithm can improve the cognitive performance of the system and defense against cooperative SSDF attacks effectively by comparing to current methods.