一种基于函数调用图的恶意软件变体检测方法

Lingfei Wu, Ming Xu, Jian Xu, Ning Zheng, Haiping Zhang
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引用次数: 8

摘要

代码混淆在变形恶意软件中起着重要的作用。此外,识别变形恶意软件变体是一项具有挑战性的任务,因为它的混淆引擎可以很容易地生成具有不同形式的各种变体,同时保持相同的功能以逃避检测。本文提出了一种基于程序函数调用图识别变形恶意软件的新方法。在函数调用图的基础上,利用图着色和余弦相似度技术来度量两个程序的相似度。实验结果表明,该方法能够准确地检测出变形的恶意软件变体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel malware variants detection method based On function-call graph
Code obfuscation plays a significant role in metamorphic malware. Moreover, identifying a metamorphic malware variant is a challenge task, because its obfuscation engine can easily generate various variants with different forms while maintaining the same functionality to escape detection. This paper presents a novel approach to recognize metamorphic malware based on programs' function-call graphs. Graph-coloring and cosine similarity techniques are used to measure the similarity of two programs on the basis of function-call graph. Experimental results have shown that the proposed method can accurately detect the metamorphic malware variants.
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