摘要
入侵检测系统一直以来都是多层安全体系架构不可或缺的一部分,与传统的防御解决方案相比,基于数据挖掘的入侵检测有着较高的精确度,并能有效的识别未知的入侵模式,然而伪肯定率的存在也一直是阻止基于数据挖掘的入侵检测系统研究深入的最大阻碍.本文分析了影响入侵检测精确度的因素,提出了一种基于数据挖掘的有效提高精确度,降低伪肯定率的入侵检测方法.
Intrusion detection system has long been recognized as a necessary component of a multilayered security architecture. Comparing with the traditional intrusion detection system, data mining-based intrusion detection has the feature of high precision, and to some extent can effectively recognize unknown attacks. However, the existence of false positives has long been a hindrance to deep research. In this paper, factors affecting the detection rate are analyzed and a method of intrusion detection system that can effectively improve precision and decrease false positive rate is presented.
出处
《北方工业大学学报》
2006年第1期1-5,20,共6页
Journal of North China University of Technology
