基于数据挖掘的网络入侵检测系统的设计与应用

网络攻击工具与手段日趋复杂多样,单纯的防火墙策略已经无法满足对安全高度敏感的部门的需要.将数据挖掘技术应用到网络入侵检测中,能够广泛地收集审计数据来计算模型,从而精确地捕获实际的入侵和正常行为模式,自动生成入侵检测规则,实现入侵检测系统的智能化.在此基础上设计并实现了一个智能化网络入侵检测系统模型,阐述了该系统模型的结构、工作原理及主要功能.该模型为开放的系统模型,具有很好的可伸缩性,可大大减少使用入侵检测系统的代价,有效地解决了入侵检测系统的环境适应性问题.

Design and Application of Intrusion Detection System Based on Data Mining

Simplex firewall strategy can′t satisfy the requests with the increasing of network attack toolsand means.In order to solve problems existing in the traditional intrusion detection systems,the paper puts forward an intelligence network intrusion detection system model based on data mining.The application of data mining technology of network intrusion detection can collect audit data to calculate the model.The system can capture the real intrusion and the normal action mode and intrusion detection is intelligent through the building of intrusion detection rules automatically.The basic theory of the model is introduced.Its structure and main function are analyzed.The model is an open system having good scalability and adaptability and can reduce the cost of deploying an intrusion detection system.The problem of environment adaptability is solved and the efficiency of system is proved.