Defending Against Massive SSDF Attacks From a Novel Perspective of Honest Secondary Users

Abstract

In cognitive radio networks (CNRs), spectrum sensing data falsification (SSDF) attacks can severely deteriorate the performance of the collaborative spectrum sensing (CSS), which may be worse compared with the performance of the independent spectrum sensing (IndSS) under massive SSDF attacks. In this letter, a novel algorithm for defending against massive SSDF attacks is investigated from the perspective of honest secondary users (HSUs). In the proposed algorithm, each HSU evaluates the reliability of the CSS results. The CSS results with high reliability value are employed by secondary users (SUs) as final sensing results. However, its own sensing results are used if reliability value of CSS results is lower than the certain threshold. Theoretical derivation for the threshold of the reliability value is explained. Simulation results verify the effectiveness of the proposed scheme and indicate that our proposed algorithm can be considered as the extension of existing anti SSDF attacks algorithms.