Research on Multi-Agent Based Network Intrusion Detection Systems
Aiming at the problem of low accuracy of traditional network intrusion detection system in recognizing complex and variable network attack patterns,a multi-intelligence body network intru-sion detection system based on independent Q-learning is proposed.The system adopts multi-intelli-gent body architecture,and each intelligent body applies independent Q-learning algorithms to monitor network behaviors and risk assessment,which improves the efficiency and accuracy of network intrusion detection through an intelligent approach.The experimental results show that compared with the tradi-tional intrusion detection methods,the detection accuracy,response speed and robustness of this system have been significantly improved,and it can effectively identify unknown attack patterns,showing good adaptive and generalization capabilities,providing a new solution for the field of network security,and it has a certain theoretical and practical value for the construction of a more intelligent and reliable network security protection system.
万方数据
维普
