On the Impact of SSDF Attacks in Hard Combination Schemes in Cognitive Radio Networks

Abstract

One of the critical threats menacing the Cooperative Spectrum Sensing (CSS) in Cognitive Radio Networks (CRNs) is the Spectrum Sensing Data Falsification (SSDF) reports, which can deceive the decision of Fusion Center (FC) about the Primary User (PU) spectrum accessibility. In CSS, each CR user performs Energy Detection (ED) technique to detect the status of licensed frequency bands of the PU. This paper investigates the performance of different hard-decision fusion schemes (OR-rule, AND-rule, and MAJORITY-rule) in the presence of Always Yes and Always No Malicious User (AYMU and ANMU) over Rayleigh and Gaussian channels. More precisely, comparative study is conducted to evaluate the impact of such malicious users in CSS on the performance of various hard data combining rules in terms of miss detection and false alarm probabilities. Furthermore, computer simulations are carried out to show that the hard-decision fusion scheme with MAJORITY-rule is the best among hard-decision combination under AYMU attacks, OR-rule has the best detection performance under ANMU.