构建恶意软件感染树

J. Morales, Michael Main, Weiliang Luo, Shouhuai Xu, R. Sandhu
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引用次数: 7

摘要

恶意软件的动态分析是一项不断发展和具有挑战性的任务。恶意软件感染树(MiT)可以通过识别与特定恶意软件样本相关的进程和文件来协助分析。在本文中,我们提出了一种抽象的方法来构建一个基于规则的综合MiT,该规则描述了恶意软件感染文件和进程策略所必需的执行事件。MiT是基于信息的传递性和创建者/被创建者的关系,使用进程和文件之间的强弱联系来构建的。抽象方法便于在任何操作系统平台上使用。我们使用名为MiTCoN的自定义工具在Windows Vista操作系统上实现规则,该工具用于小规模分析和感染树创建,其中包含5800个已知恶意软件样本。结果分析表明,我们的规则在很短的时间内发生了重大变化。我们证明了我们的规则集可以有效和高效地构建感染树,链接特定恶意软件样本的所有相关进程和文件,没有误报。我们还测试了MiT在系统消毒中的可用性,成功率为100%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Building malware infection trees
Dynamic analysis of malware is an ever evolving and challenging task. A malware infection tree (MiT) can assist in analysis by identifying processes and files related to a specific malware sample. In this paper we propose an abstract approach to building a comprehensive MiT based on rules describing execution events essential to malware infection strategies of files and processes. The MiT is built using strong and weak bonds between processes and files which are based on transitivity of information and creator/created relationships. The abstract approach facilitates usage on any operating system platform. We implement the rules on the Windows Vista operating system using a custom built tool named MiTCoN which was used in a small scale analysis and infection tree creation of a diverse set of 5800 known malware samples. Results analysis revealed a significant occurrent of our rules within a very short span of time. We demonstrate our rule set can effectively and efficiently build infection trees linking all related processes and files of a specific malware sample with no false positives. We also tested the possible usability of a MiT in disinfecting a system which yielded a 100% success rate.
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