Team Cooperative Attack Planning Based on Multi-agent Joint Decision

• Published in: Ji suan ji ke xue Vol. 48; no. 5; p. 301
• Main Authors: Zhou, Tian-Yang, Zeng, Zi-Yi, Zang, Yi-Chao, Wang, Qing-Xian
• Format: Journal Article
• Language: Chinese
• Published: Chongqing Guojia Kexue Jishu Bu 01.01.2021
• Subjects: Algorithms; Automation; Decision making; Mathematical analysis; Matrix methods; Multiagent systems; Operations research; Path planning; Penetration
• ISSN: 1002-137X

Automated penetration testing can greatly reduce the cost of penetration testing by automating the process of manually finding possible attack paths.Existing methods mainly use a single agent to perform attack tasks, which leads to long execution of attack actions and low penetration efficiency.If multi-agent cooperative attack is considered, the state space scale of planning problem will grow exponentially due to the multi-dimensional local state of each agent.Aiming at the above problems, a team cooperative attack planning method based on multi-agent jointdecision is proposed.Firstly, the multi-agent cooperative attack path planning problem is transformed into the attack target assignment problem under the jointdecision constraints, and the multi-agent centralized decision-making mode is established.Secondly, the joint decision vector matrix JDVM is used to calculate the penetration attack reward based on the CDSO-CAP model, and the greedy strategy is used to search the optimal target of attack.The experime