基于人工智能理论的网络安全管理关键技术的研究

Research on Key Technologies of Network Security Management Based on Theory of Artificial Intelligence

网络安全对网络应用具有非常重要性的现实意义,其中,网络异常检测和泛化能力是网络安全管理中的关键环节。以基于人工智能理论的网络安全管理关键技术为研究对象,提出基于克隆选择模糊聚类算法的异常检测方法,解决异常检测效率低、误报率高等问题;提出基于交补分担准则的证据组合规则方法,解决信息融合证据组合冲突和规则缺陷等问题;提出基于改进证据组合规则的P2P信任管理模型,解决P2P系统难以有效处理恶意节点攻击、不能有效处理不确定性信息等问题。

Network security is the great important practical meanings on the network, which network anomaly detection and network security management generalization ability are the key link. In this paper, the theory of artificial intelligence is based on the network security management key technologies for the study, clonally selection fuzzy clustering algorithm is made based on anomaly detection, anomaly detection efficiency to solve the low rate of false positives and other issues, providing evidence-based guidelines to pay up share portfolio rule approach to solve conflicts and information fusion evidence combination rule defects and other problems. Combination rules of evidence suggest improvements P2P trust management model based on P2P systems can not effectively deal with solving the malicious node attacks, and also can not effectively deal with uncertain information and other issues.