拖延的力量:检测和减轻执行拖延的恶意代码

C. Kolbitsch, E. Kirda, Christopher Krügel
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引用次数: 107

摘要

恶意软件仍然是当今互联网上最重要的安全问题之一。每当反恶意软件解决方案流行起来时,恶意软件作者通常会迅速做出反应并修改其程序以逃避防御机制。例如,最近,恶意软件作者越来越多地开始创建可以逃避动态分析的恶意代码。最近一种针对动态分析系统的规避形式是拖延代码。拖延代码通常在任何恶意行为之前执行。攻击者的目标是将恶意活动的执行延迟足够长的时间,以便自动动态分析系统无法提取出有趣的恶意行为。本文提出了检测和减轻恶意拖延代码的第一种方法,并确保在分配给样本分析的时间内取得进展。实验结果表明,我们的系统(称为accelerate)在实践中运行良好,并且能够在真实的恶意软件样本中检测到额外的恶意行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The power of procrastination: detection and mitigation of execution-stalling malicious code
Malware continues to remain one of the most important security problems on the Internet today. Whenever an anti-malware solution becomes popular, malware authors typically react promptly and modify their programs to evade defense mechanisms. For example, recently, malware authors have increasingly started to create malicious code that can evade dynamic analysis. One recent form of evasion against dynamic analysis systems is stalling code. Stalling code is typically executed before any malicious behavior. The attacker's aim is to delay the execution of the malicious activity long enough so that an automated dynamic analysis system fails to extract the interesting malicious behavior. This paper presents the first approach to detect and mitigate malicious stalling code, and to ensure forward progress within the amount of time allocated for the analysis of a sample. Experimental results show that our system, called HASTEN, works well in practice, and that it is able to detect additional malicious behavior in real-world malware samples.
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CiteScore
9.20
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