Investigating the Effectiveness of Spectrum Sensing Data Falsification Attacks Defense Mechanisms in Cognitive Radio Ad Hoc Networks

Abstract

Cognitive Radio Networks (CRN) was proposed to improve the utilization of wireless spectrum resources. However, it is susceptible to various security attacks like any other wireless network. CRN technology allows secondary users (SU) to opportunistically utilize the idle spectrum while avoiding interfering with primary users (PU). Spectrum sensing is a key characteristic of this technology and it is the main enabling functionality in facilitating the utilization of free channels by PUs and SUs. Unfortunately, malicious users can interfere with either the PUs or SUs. Spectrum Sensing Data Falsification (SSDF) attack is one of the major attacks in CRN which result in incorrect wrong spectrum access decisions being made which result in interference. There is therefore a need to investigate this attack and design robust SSDF mitigation schemes. In this study, we investigate different approaches to prevent or mitigate SSDF attack and evaluate comparative results of two best mitigation schemes in literature and make recommendations for future research. Three metrics were used for evaluation. These are: missed detection, success and false alarm probabilities which were used to evaluate the performance of the schemes. It is shown though MATLAB simulation results that extreme studentized cooperative consensus spectrum sensing performs better compared to the reputation-based and majority ruling scheme.