GPDS: A multi-agent deep reinforcement learning game for anti-jamming secure computing in MEC network

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成果类型：

期刊论文

作者：

Chen, Miaojiang;Liu, Wei;Zhang, Ning;Li, Junling;Ren, Yingying;...

通讯作者：

Liu, W.

作者机构：

[Ren, Yingying; Chen, Miaojiang; Liu, Anfeng] Cent South Univ, Sch Comp Sci & Engn, Changsha 410083, Peoples R China.

[Liu, Wei] Hunan Univ Chinese Med, Sch Informat, Changsha 410208, Hunan, Peoples R China.

[Zhang, Ning] Univ Windsor, Dept Elect & Comp Engn, 401 Sunset, Windsor, ON, Canada.

[Li, Junling] Univ Waterloo, Dept Elect & Comp Engn, 200 Univ Ave, Waterloo, ON, Canada.

[Yi, Meng] Southeast Univ, Schooltemp Comp Sci & Engn, Nanjing, Peoples R China.

通讯机构：

School of Informatics, Hunan University of Chinese Medicine, Hunan, Changsha, China

语种：

英文

关键词：

Deep reinforcement learning;Multi-agent;Secure computing;Decision-making;Mobile Edge Computing (MEC)

期刊：

Expert Systems with Applications

ISSN：

0957-4174

年：

2022

卷：

210

页码：

118394

DOI：

10.1016/j.eswa.2022.118394

基金类别：

National Natural Science Foundation of China [62072475, 61772554]; Open Research Project of the State Key Laboratory of Industrial Control Technology, Zhejiang University, China [ICT2022B15]; Hu-nan Provincial Innovation Foundation for Postgraduate, China

机构署名：

本校为其他机构

摘要：

The openness of Mobile Edge Computing (MEC) networks makes them vulnerable to interference attacks by malicious jammers, which endangers the communication quality of mobile users. To achieve secure computing, the conventional method is that the mobile device reduces the attacker's malicious interference by increasing the transmission power. However, the cost of power defense is unacceptable in MEC with resource shortages. Therefore, this paper considers a novel defense strategy based on time-varying channel and describes the malicious interfere...

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GPDS: A multi-agent deep reinforcement learning game for anti-jamming secure computing in MEC network

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