Error detection of malicious user attack in cognitive radio networks

Abstract

Malicious user is internal attacker that disturb communication. In case of cognitive radio, malicious user attacks primary signal detection and influences the fidelity of sensing outcome. This paper studies malicious user attack and its impacts to sensing outcome in cognitive radio network (CRN). We consider a number of malicious user that emulate primary user (PU) signal. Malicious users are randomly deployed around secondary user (SU) at a certain distance. The distance between PU transmitter and SU is 100 km. We define different number of malicious user and observe the impact to detection error rate. The change of transmission power of malicious user is also studied. These two cases is investigated under two hypothesis of Neyman Pearson criterion. The derived results show that increasing number of malicious user can increase probability of error rate. Furthermore, increasing power transmission of malicious user can increase probability of error rate as well.