基于局域网的人工智能安全信息访问控制系统设计

Design of Artificial Intelligence Security Information Access Control System Based on Local Area Network

近年来,受到网络环境复杂化、多元化变革的影响,局域网系统的运行安全性与稳定性遭受了严重威胁。为解决局域网安全隐患问题,文章以人工智能技术中的克隆选择模糊聚类算法为切入点,设计了一种适配于大部分局域网应用场景的信息安全访问控制系统。最终测试结果表明,在局域网环境中应用该系统能够有效检测出各类风险隐患,其中系统对内部用户的违规行为的捕捉精准度更是能够达到90%以上,并且对各类信息的检测与处理效率较高,最高每秒可以处理2 500条消息,具备持续研究与应用、推广的价值。

In recent years,due to the complexity and diversification of the network environment,the operational security and stability of local area network systems have been seriously threatened.To solve the problem of complete hidden dangers in local area networks,this article takes the clone selection fuzzy clustering algorithm in artificial intelligence technology as the starting point and designs an information security access control system that is suitable for most local area network application scenarios.The final test results show that the system can effectively detect various risks and hidden dangers in a local area network environment.The accuracy of the system's capture of internal user violations can reach over 90%,and the detection and processing efficiency of various types of information is high.It can process up to 2500 messages per second,which has the value of continuous research,application,and promotion.