摘要
传统的入侵检测技术在扩展性和适应性上已不能应付越来越复杂的攻击方式,利用模糊聚类方法可以在入侵检测中生成更好的检测规则,提出了FCM的改进算法SFCM,设计并实现了基于SFCM的入侵检测系统FCIDS,利用KDD CUP99数据进行实验,结果表明能够显著提高检测率和降低误报率。
The traditional intrusion detection system （IDS） is limited in the extensibility and the adaptability. The better checking rules can be used in intrusion detection system with fuzzy clustering and an improved fuzzy clustering algorithm sFcM （shift fuzzy C means） is presented. The intrusion detection system FCIDS（ fuzzy clustering based intrusion detection system） based on algorithm SFCM is designed and implemented. The correctness and the validity of FCIDS are identified through the experiments for the KDD CUP99 datasets.
出处
《江苏广播电视大学学报》
2007年第3期58-60,共3页
Journal of Jiangsu Radio & Television University
基金
江苏省自然科学基金项目(BK2005135)
关键词
入侵检测
模糊聚类
数据挖掘
intrusion detection
fuzzy clustering
data mining
