Towards Artificial Intelligence Empowered Security and Privacy Issues in 6G Communications
Ajay Bandi, Sowmya Yalamarthi
Abstract
Applications of wireless networks beyond 5G are vulnerable to various security and privacy concerns. This research aims to identify the security and privacy flaws beyond 5G network applications and their defense mechanisms. This research study has reviewed 44 research articles and presented the taxonomy of several concerns in security and privacy of artificial intelligence and machine learning empowered 6G applications. Furthermore, this study has identified the defense mechanism technologies for such issues. A few defense mechanism approaches are homographic encryption, physical layer authentication, biometric authentication, explainable, trustworthy, and superintelligent AI. The implications of this study are applicable to prevent attacks, eavesdropping, jamming, and other security and privacy concerns when developing wireless networks.