ABSTRACT
Cooperative spectrum sensing (CSS) and cognitive radio (CR) are the best resolutions for a spectrum shortage in 5G wireless networks. In this chapter, a novel machine learning method is discussed for securing a 5G-based CR communication network. CSS reduces device-sensing difficulty and magnifies the spectrum sensing accuracy. CSS is threatened by a special attack called spectrum sensing data falsification (SSDF) attack. This attack is a link layer attack in OSI data communications. The chapter includes a machine learning algorithm to solve the SSDF attack and rule-based approaches to classify secondary users (SUs) to perform the security task easily. This chapter includes five recent existing approaches and compares the results with the proposed machine learning method called ‘improved-apriori’ algorithm. The proposed method outperforms the five recent existing methods effectively.
