Adaptive and Dynamic Security in AI-Empowered 6G: From an Energy Efficiency Perspective

Emerging AI-empowered services and techniques, such as connected vehicle, intelligent industry, and smart city, are forthcoming with the sixth generation (6G) cellular network to benefit daily life, industry, and society. However, the increasing integration of the 6G network with the physical world leads to a plethora of new scenarios that bring new challenges to 6G, especially from the security and energy aspects. In 5G networks, security solutions across all devices and base stations are configured with universal settings for certain types of attacks. This one-size-fit-all strategy no longer suits 6G security due to the higher diversity in device capabilities, service features, energy conditions, attack vulnerabilities, and other time-varying attributes. Since each scenario may have unique security requirements and energy availability, the selection and configuration of security strategies need to be optimized for 6G networks in an adaptive and dynamic manner. In this article, we explore 6G security from an energy efficiency perspective by balancing the tradeoff between security and energy consumption in various scenarios. Specifically, we first investigate the AI-empowered 6G network architecture with promising applications and visions. Then we identify the challenges for adaptive and dynamic security optimization in 6G from the aspects of heterogeneity, dynamics, and modeling complexity. To balance security-energy trade-off, we propose an optimization framework that provides customized recommendations of security strategy to different user devices and base stations. Finally, open issues are discussed on 6G security from an energy efficiency perspective.