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Behavior-Based Malware Analysis and Detection

机译:基于行为的恶意软件分析和检测

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摘要

Malware, such as Trojan Horse, Worms and Spy ware severely threatens Internet. We observed that although malware and its variants may vary a lot from content signatures, they share some behavior features at a higher level which are more precise in revealing the real intent of malware. This paper investigates the technique of malware behavior extraction, presents the formal Malware Behavior Feature (MBF) extraction method, and proposes the malicious behavior feature based malware detection algorithm. Finally we designed and implemented the MBF based malware detection system, and the experimental results show that it can detect newly appeared unknown malwares.
机译:特洛伊木马,蠕虫和间谍软件等恶意软件严重威胁了Internet。我们观察到,尽管恶意软件及其变体与内容签名可能有很大不同,但它们在更高级别上共享某些行为功能,这些行为功能可以更精确地揭示恶意软件的真实意图。本文研究了恶意软件行为提取技术,提出了形式化的恶意软件行为特征(MBF)提取方法,并提出了基于恶意行为特征的恶意软件检测算法。最后,我们设计并实现了基于MBF的恶意软件检测系统,实验结果表明,它可以检测到新出现的未知恶意软件。

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