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随着计算机网络应用的普及和网络活动的日益频繁,计算机的安全问题日益突出。入侵检测系统是信息安全技术中的重要组成部分。然而,传统的入侵检测系统在有效性、适时性和可扩展性方面都存在不足。本文根据数据挖掘的知识,提出基于模糊聚类技术的入侵检测系统模型,并对此模型进行深入研究。仿真证明,该方法对已知或未知的入侵行为都有较好的检测效果,能够检测到其它入侵检测算法不易检测到的入侵行为。
With the popularization of computer network applications and the increasing frequency of network activities, computer security problems have become increasingly prominent. Intrusion detection system is an important part of information security technology. However, the traditional intrusion detection system is not effective, timely and scalability. Based on the knowledge of data mining, this paper proposes an intrusion detection system model based on fuzzy clustering technology, and deeply studies the model. The simulation results show that this method has good detection effect on both known and unknown intrusion behaviors and can detect intrusion behaviors that are not easily detected by other intrusion detection algorithms.