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A heuristic approach for detection of obfuscated malware

机译:一种启发式方法,用于检测混淆的恶意软件

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Obfuscated malware has become popular because of pure benefits brought by obfuscation: low cost and readily availability of obfuscation tools accompanied with good result of evading signature based anti-virus detection as well as prevention of reverse engineer from understanding malwares' true nature. Regardless obfuscation methods, a malware must deobfuscate its core code back to clear executable machine code so that malicious portion will be executed. Thus, to analyze the obfuscation pattern before unpacking provide a chance for us to prevent malware from further execution. In this paper, we propose a heuristic detection approach that targets obfuscated Windows binary files being loaded into memory - prior to execution. We perform a series of static check on binary file's PE structure for common traces of a packer or obfuscation, and gauge a binary's maliciousness with a simple risk rating mechanism. As a result, a newly created process, if flagged as possibly malicious by the static screening, will be prevented from further execution. This paper explores the foundation of this research, as well as the testing methodology and current results.
机译:混淆后的恶意软件由于混淆带来的纯粹好处而变得流行:混淆工具的低成本和便捷可用性,以及逃避基于签名的防病毒检测的良好结果,以及防止反向工程师了解恶意软件的真实性质。无论采用哪种混淆方法,恶意软件都必须将其核心代码反混淆以清除可执行的机器代码,以便执行恶意部分。因此,在解压缩之前分析混淆模式为我们提供了防止恶意软件进一步执行的机会。在本文中,我们提出了一种启发式检测方法,该方法的目标是在执行之前将模糊的Windows二进制文件加载到内存中。我们对二进制文件的PE结构执行一系列静态检查,以查找打包程序或混淆的常见痕迹,并使用简单的风险评估机制来评估二进制文件的恶意性。结果,如果新创建的进程被静态筛选标记为可能是恶意的,则将阻止其进一步执行。本文探讨了这项研究的基础,以及测试方法和当前结果。

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