Detecting Primary User Emulation Attacks Based on PDF-BP Algorithm in Cognitive Radio Networks

摘要

Cognitive radio networks (CRNs) are vulnerable to various attacks. Primary user emulation attack (PUEA) is one kind of serious attacks. In order to combat PUEA, we propose an algorithm to detect PUEA in CRNs based on probability density function (PDF) assisted by belief propagation (BP), called PDF-BP. In the proposed algorithm, every secondary user (SU) calculates its belief value based on the PDF of the received signals and exchanges messages equally without the help of location information of primary user (PU) and extra expense on hardware and each SU makes a decision according to its belief value. Simulation results show that the proposed algorithm has detected the PUE attacker effectively.