基于元警报序列挖掘的自动攻击场景构建

Guo Fan, Yu Min
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引用次数: 1

摘要

研究人员一直在使用入侵场景来呈现高度抽象的复杂攻击过程,而据我们所知,还没有一种场景能够在线生成。提出了一种自动构建入侵场景的方法。该方法首先根据原始警报的源、目的IP对和优先级,将原始警报聚类成不同的元警报序列,从元警报序列中挖掘频繁闭合序列构建场景,然后根据场景之间的支持度挖掘场景之间的关联规则。在Darpa99和Darpa2000上的实验表明,该方法可以有效地发现攻击程序并在线运行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Attack Scenario Construction by Mining Meta-alert Sequences
Researchers have been using intrusion scenarios tore present complicated attack procedures at a high abstract level, while, to our best knowledge, none is able to produce the scenarios online. An automatic intrusion scenario construction method is proposed in the paper. According to the source and destination IP pair, and priority of the raw alerts, the method firstly clusters them into different meta-alert sequences, from which frequent closed sequences are mined to construct scenarios, after that, correlation rules between scenarios are mined based on their support.Experiments on Darpa99 and Darpa2000 shows the method can be used to effectively discover attack procedures and run online.
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