Wireless Security Enhancement Framework Based on AI and RIS in Industrial IoT Networks

Reconfigurable Intelligent Surface (RIS) technology, closely integrated with Artificial Intelligence (AI) as one of the Physical Layer (PL) technology approaches, is considered an effective solution for enhancing security in industrial Internet of Things (IIoT) networks. Integrating RIS, AI, and heterogeneous IIoT networks presents a promising approach to improving the security of wireless communications in IIoT. This paper discusses new AI-based Physical Layer Authentication (PLA) approaches and how they can be integrated with RIS to enable identity authentication and malicious node detection, aiming to provide light-weight isolation in IIoT terminals. An anti-jamming and secure communication framework for IIoT is proposed, which leverages Deep Reinforcement Learning (DRL) and RIS to defend against malicious jamming and eavesdropping targeting legitimate users’ channels. Additionally, a foundational framework that employs Quantum Reinforcement Learning (QRL) is presented to improve RIS-assisted secure communication. Furthermore, the threats posed by Generative AI (GAI) to RIS-assisted IIoT communication networks and possible defense schemes are provided. Finally, the paper concludes by discussing research opportunities and future challenges.