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Packer identificationmethod based on byte sequences

机译:基于字节序列的打包程序识别方法

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With the growing number of malware, malware analysis technologies need to be advanced continuously. Malware authors use various packing techniques to hide their code from malware detection tools and techniques. The packing techniques are generally used to compress and encrypt executable code in executable files, and the unpacking code is usually embedded in the executable files. Therefore, packed executable files can be executed by itself, and the information associated with packing can be used to analyze and detect malware. Since different packing tools will generate different packed executable files, packing tools can be identified by analyzing packed executable files, and packer identification can reduce malware-analyzing overheads, and the executable files can even be unpacked. However, most previous studies focused on packing detection using signatures of unpacking code, and these approaches can be avoided by placing unpacking code in other locations or by distributing unpacking code in multiple locations. In this paper, we propose a new packer identification method by analyzing only code sections to extract features of malware generated by different packing tools. Experimental results show that our approach can identify different packing tools with the accuracy of 91.6% on average. Considering packer identification is the harder problem than packing detection, we argue that our approach can contribute to reducing overheads of malware analysis.
机译:随着恶意软件数量的增加,恶意软件分析技术需要不断提高。恶意软件作者使用各种打包技术来将其代码隐藏在恶意软件检测工具和技术中。打包技术通常用于压缩和加密可执行文件中的可执行代码,并且解压缩代码通常嵌入在可执行文件中。因此,打包的可执行文件可以自己执行,与打包相关的信息可以用于分析和检测恶意软件。由于不同的打包工具将生成不同的打包的可执行文件,因此可以通过分析打包的可执行文件来识别打包工具,并且打包程序的标识可以减少恶意软件分析的开销,甚至可以解压缩可执行文件。但是,大多数以前的研究都集中在使用拆包代码签名进行装箱检测,并且可以通过将拆包代码放在其他位置或在多个位置分布拆包代码来避免这些方法。在本文中,我们提出了一种仅通过分析代码段以提取由不同打包工具生成的恶意软件特征的新打包程序识别方法。实验结果表明,我们的方法可以识别不同的包装工具,平均精度为91.6%。考虑到打包程序识别比打包检测更难,我们认为我们的方法可以有助于减少恶意软件分析的开销。

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