AI Driven Security Threat Analysis for 5G Cognitive Radio Short Range Applications
Keywords:
5G, Cognitive Radio, Short range application, Security analysis, Artificial intelligence, Chaotic deep belief networks.Abstract
With 5G technologies, cognitive radio (CR) has become a possible answer to maximize spectrum utilization and efficiency. But in the case of short range application particularly, CR also brings significant security concerns in addition to benefits. Emphasizing short range use, this paper user 5G frame works to assess the security issue with cognitive radio systems. Among the discovered security hazards are primary user emulation attack, jamming attacks, SSDF attacks etc.; driven by reputation. Chaotic Deep Belief Networks (DBN) for detection and mitigation purpose is proposed to overcome these challenges using artificial intelligence (AI) approaches. Emphasizing the need of strong security measures to ensure the integrity and dependability of communication network, the analysis considers the unique characteristics of 5G –CR spectrum and short range applications .the result shows that the proposed chaotic DBN classification approach had accuracy ranging from 92.5 % to 94.2% in the testing set and an accuracy of 95.5% on the training set.
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