Secure and reliable cooperative spectrum sensing in the presence of massive probabilistic Byzantine attacks

In cognitive radio networks (CRNs), cooperative spectrum sensing (CSS) improves spectrum sensing performance in radio environments subject to fading and shadowing. However, when some secondary users (SUs) share falsified sensing information in CSS through a falsification attack on sensing data (spectrum sensing data falsification attack, SSDF), the sensing performance degrades significantly. This document proposes a new probabilistic SSDF attack model and a new defence strategy based on a robust identification and suppression mechanism against massive SSDF attacks. Simulation results obtained under various massive probabilistic SSDF attack scenarios show that the detection performance of the proposed defence scheme outperforms that of the weighted sequential probability ratio test (WSPRT), sequential probability ratio test (SPRT), and Majority fusion techniques with which comparisons have been made. The proposed defence scheme guarantees a near-zero probability of error whatever the number of attackers and whatever the SSDF attack strategy, which is not the case for WSPRT, SPRT, and Majority rule.