Scenario based threat detection and attack analysis

P. Hsiu, Chin-Fu Kuo, Tei-Wei Kuo, E.Y.T. Juan
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引用次数: 6

Abstract

This paper targets two essential issues in intrusion detection system designs: the optimization of rule selection and the attack discovery in attack analysis. A scenario-based approach is proposed to correlate malicious packets and to intelligently select intrusion detection rules to fire. We propose algorithms for rule selection and attack scenario identification. Potential threats and their relationship for a gateway and Web-server applications are explored as an example in the study. The proposed algorithms are implemented over Snort, a signature-based intrusion detection system, for which we have some encouraging performance evaluation results.
基于场景的威胁检测和攻击分析
本文针对入侵检测系统设计中的两个关键问题:规则选择的优化和攻击分析中的攻击发现问题。提出了一种基于场景的方法来关联恶意数据包,并智能选择入侵检测规则来触发。我们提出了规则选择和攻击场景识别算法。本研究以网关和web服务器应用程序的潜在威胁及其关系为例进行了探讨。所提出的算法是在Snort上实现的,Snort是一种基于签名的入侵检测系统,我们对其进行了一些令人鼓舞的性能评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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