| Title | Game Theory Based Multi-agent Cooperative Anti-jamming for Mobile Ad Hoc Networks |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Ma, Yaodong, Liu, Kai, Luo, Xiling |
| Conference Name | 2022 IEEE 8th International Conference on Computer and Communications (ICCC) |
| Date Published | dec |
| Keywords | anti-jamming, distributed, game theoretic security, Games, Heuristic algorithms, Human Behavior, human factors, Knowledge engineering, Markov game, Markov processes, Metrics, mobile ad hoc networks, multi-agent cooperation, pubcrawl, q-learning, reinforcement learning, reliability theory, Scalability, simulation |
| Abstract | Currently, mobile ad hoc networks (MANETs) are widely used due to its self-configuring feature. However, it is vulnerable to the malicious jammers in practice. Traditional anti-jamming approaches, such as channel hopping based on deterministic sequences, may not be the reliable solution against intelligent jammers due to its fixed patterns. To address this problem, we propose a distributed game theory-based multi-agent anti-jamming (DMAA) algorithm in this paper. It enables each user to exploit all information from its neighboring users before the network attacks, and derive dynamic local policy knowledge to overcome intelligent jamming attacks efficiently as well as guide the users to cooperatively hop to the same channel with high probability. Simulation results demonstrate that the proposed algorithm can learn an optimal policy to guide the users to avoid malicious jamming more efficiently and rapidly than the random and independent Q-learning baseline algorithms, |
| DOI | 10.1109/ICCC56324.2022.10065839 |
| Citation Key | ma_game_2022 |
Game Theory Based Multi-agent Cooperative Anti-jamming for Mobile Ad Hoc Networks