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A semantics-based approach to malware detection

机译:基于语义的恶意软件检测方法

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摘要

Malware detection is a crucial aspect of software security. Current malware detectors work by checking for "signatures," which attempt to capture (syntactic) characteristics of the machine-level byte sequence of the malware. This reliance on a syntactic approach makes such detectors vulnerable to code obfuscations, increasingly used by malware writers, that alter syntactic properties of the malware byte sequence without significantly affecting their execution behavior.This paper takes the position that the key to malware identification lies in their semantics. It proposes a semantics-based framework for reasoning about malware detectors and proving properties such as soundness and completeness of these detectors. Our approach uses a trace semantics to characterize the behaviors of malware as well as the program being checked for infection, and uses abstract interpretation to "hide" irrelevant aspects of these behaviors. As a concrete application of our approach, we show that the semantics-aware malware detector proposed by Christodorescu et al. is complete with respect to a number of common obfuscations used by malware writers.
机译:恶意软件检测是软件安全性的关键方面。当前的恶意软件检测器通过检查“签名”来工作,“签名”试图捕获(语法上的)恶意软件的机器级字节序列的特征。这种对语法方法的依赖使此类检测器容易受到恶意软件编写者越来越多使用的代码混淆的影响,从而在不显着影响其执行行为的情况下改变了恶意软件字节序列的语法属性。语义。它提出了一个基于语义的框架,用于推理恶意软件检测器并证明这些检测器的健全性和完整性。我们的方法使用跟踪语义来表征恶意软件的行为以及正在检查感染程序的行为,并使用抽象解释来“隐藏”这些行为的不相关方面。作为我们方法的具体应用,我们展示了Christodorescu等人提出的语义感知恶意软件检测器。关于恶意软件编写者使用的许多常见混淆,本文已经完成。

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