Cooperative spectrum sensing in the presence of primary user emulation attack in cognitive radio network: multi-level hypotheses test approach

Abstract

The inherent nature of cognitive radio (CR) networks has brought new threats to wireless communications. Primary user emulation attack (PUEA) has been widely studied as a serious threat to cooperative spectrum sensing (CSS) in CR networks. In PUEA, a malicious user can obstruct CR users from accessing idle frequency bands by imitating licensed primary user (PU) signal characteristics. The present study introduces a new CSS scheme in the presence of a malicious PUEA based on multi-level hypothesis testing (MLHT). In the proposed method, generalizing from binary hypothesis testing to MLHT, we partition the decision space to four decision options and apply minimum Bayes cost criteria to determine the channel status. We also discuss practical limitation issues that need to be considered when applying the MLHT approach. Simulation results are provided to indicate the performance improvement of the proposed MLHT method against PUEA, compared with the conventional method.

Multiple-Phase Energy Detection and Effective Capacity Based Resource Allocation Against Primary User Emulation Attacks in Cognitive Radio Networks

“…(1) follows the Chi-square distribution with a degree of freedom of . However, according to the Central Limit Theorem (CLT), can be approximated by a Gaussian distribution with a long enough N. Actually, CLT has been usually applied to simplify the analysis and design in the spectrum sensing, such as in [9], [11] and [19]. Further, the authors of [9] and [11] considered that CLT could be used when N >10.…”

“…Concretely, the main parameters involved in cooperative spectrum sensing, such as the number of samples, the detection thresholds for the SU's local decision and the parameter K in voting rule, were optimized to minimize the sensing error probability in the works of [8] and [9]. To retain more information of the local observations at each SU, soft decision fusion (SDF) schemes were studied also to realize the accurate PU detection in the presence of PUEA in [10], [11]. The local measured statistic of each SU rather than the binary decision result is sent to FC and a global decision is made by FU based on the original measurements of multiple SUs.…”

“…Further, the weights were optimized to maximize the SU's throughput. While, the work in [11] applied minimum Bayes cost criteria to determine the channel status in four cases. In addition, a selfish SU attack was discussed in [12].…”

Intelligent threshold selection in fading environment of cognitive radio network: Advances in throughput and total error probability

“…Moreover, Lu et al 41 have improved the detection probability of CU through employing adaptive sensing window and spectrum utilization by allowing simultaneous sensing and data transmission in CSS. Therefore, Yadav et al and Sharifi et al 31,32 have employed the multilevel hypothesis and improved the sensing performance of CU under CSS for above-mentioned scenario. Moreover, it has been illustrated that the performance of CSS degraded under PU emulation attack.…”

“…Moreover, it has been illustrated that the performance of CSS degraded under PU emulation attack. Therefore, Yadav et al and Sharifi et al 31,32 have employed the multilevel hypothesis and improved the sensing performance of CU under CSS for above-mentioned scenario. Fan and Jiang 35 have proposed an approach to compute the total sensing period for CU in multichannel CSS and provided the method to distribute the total sensing period among different channels to maximize the throughput.…”