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A Static Method for Detection of Information Theft Malware

机译:信息盗窃恶意软件的静态检测方法

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摘要

Existing techniques based on behavior semantics for information theft malware detection have the main shortcomings of low path coverage and disability of finding hidden malicious behaviors. In this paper we propose a static method for the detection of information theft malware to overcome these shortcomings. It is particularly efficienct for inter-procedure taint analysis, and it is suitable for complicated malware detection, such as Trojan and Bot. Its static style makes it able to find hidden malicious behaviors. We also present an implementation of our method that works on x86 executables and a set of experimental studies validate its good efficiency and effectiveness.
机译:用于信息盗窃恶意软件检测的基于行为语义的现有技术的主要缺点是路径覆盖率低以及无法发现隐藏的恶意行为。在本文中,我们提出了一种静态方法来检测信息盗窃恶意软件,以克服这些缺点。它对于过程间污点分析特别有效,并且适用于Trojan和Bot等复杂的恶意软件检测。它的静态样式使其能够发现隐藏的恶意行为。我们还介绍了可在x86可执行文件上运行的方法的实现,并且一组实验研究证明了其良好的效率和有效性。

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