In this paper, we consider a wireless resource allocation problem in a cyber-physical system (CPS) where the control channel, carrying resource allocation commands, is subjected to denial-of-service (DoS) attacks. We propose a novel concept of collaborative distributed and centralized (CDC) resource allocation to effectively mitigate the impact of these attacks. To optimize the CDC resource allocation policy, we develop a new CDC-deep reinforcement learning (DRL) algorithm, whereas existing DRL frameworks only formulate either centralized or distributed decision-making problems. Simulation results demonstrate that the CDC-DRL algorithm significantly outperforms state-of-the-art DRL benchmarks, showcasing its ability to address resource allocation problems in large-scale CPSs under control channel attacks.
@article{arxiv.2411.10702,
title = {Wireless Resource Allocation with Collaborative Distributed and Centralized DRL under Control Channel Attacks},
author = {Ke Wang and Wanchun Liu and Teng Joon Lim},
journal= {arXiv preprint arXiv:2411.10702},
year = {2024}
}
Comments
This work has been submitted to the IEEE for possible publication