Systematization of metrics in intrusion detection systems

Yufan Huang, Xiaofan He, H. Dai
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引用次数: 3

Abstract

Intrusion detection assumes paramount importance in this information era due to its capability of providing security protection to information systems. In addition to advancing the specific intrusion detection techniques, substantial efforts have been devoted to the taxonomy of existing IDSs, mostly focusing on the methodology, audit source and architecture aspects. The employed metric is another decisive factor of IDS performance, yet a systematized understanding in this aspect is still lacking. As an initial effort towards this objective, a categorization of IDS metrics is proposed in this work, where existing IDS metrics are divided into four types - information theoretic, probabilistic, proximity-based, and reliability-based metrics. Simulation studies of several intrusion detection algorithms that match the proposed categorization are also conducted based on the KDD'99 dataset.
入侵检测系统中度量的系统化
入侵检测能够为信息系统提供安全保护,在信息时代显得尤为重要。除了推进特定的入侵检测技术之外,还对现有入侵防御系统的分类进行了大量的研究,主要集中在方法、审计源和体系结构方面。所采用的指标是IDS性能的另一个决定性因素,但在这方面仍然缺乏系统的理解。作为实现这一目标的初步努力,本工作提出了IDS度量的分类,其中现有的IDS度量分为四种类型-信息论,概率,基于接近性和基于可靠性的度量。基于KDD'99数据集,对几种与所提分类相匹配的入侵检测算法进行了仿真研究。
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