Advanced Q-Learning-Based Dynamic Key Distribution for Secure Wireless Communication IoT Networks

Abstract

Secure IoT network-based dynamic key distribution using Q-learning techniques. IoT networks play a vital role in contemporary wireless communication systems, so developing efficient security mechanisms is crucial in a world where the number of smart devices is increasing dramatically. Reinforcement learning based solution However, this paper proposed a reinforcement learning based solution, in which a Q-learning based key distribution approaches is presented to adapt with the changing security requirements of different IoT devices. Here, each IoT device learns to broadcast keys according to multi-agent reinforcement learning problem to prevent threats and not only this but improve overall network security. We validate the method through extensive simulations showing significant improvements in performance on key management and threat mitigation. Our findings indicate that the shrewd integration of dynamic key distribution with reinforcement learning can serve as a most effective approach to safeguard contemporary IoT ecosystems from diverse cyber-attacks.