AI-Augmented Cybersecurity Protocols for Secure Multi-Hop Wireless Communication in 6G Networks

The authors presented a holistic AI-augmented cybersecurity protocol architecture for trustworthy multi-hop wireless communication system in 6G networks. They follow an approach that builds secure and efficient communication in dynamic and resource constraint settings from implementing Deep Learning, Federated Learning, and Reinforcement Learning. The combination of these techniques helps ensure prompt detection of threats, flexible management of security controls, and cost-effective use of resources. Extensive simulations and evaluations confirm that the protocol provides improved performance in terms of detection accuracy, low latency, and scalability. The results highlight that AI-driven techniques can provide holistic solutions to secure future wireless communicational systems, thus offering dynamic and long-lasting security solutions.