TagClass:一个通过增量解析从大量恶意软件标签中提取类别确定标签的工具

Y. Jiang, Gaolei Li, Shenghong Li
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引用次数: 0

摘要

VirusTotal通过提供来自大量反恶意软件引擎的恶意软件标签,被广泛用于恶意软件注释。使用这些不一致标签的一个长期挑战是提取类决定的标签。在本文中,我们介绍了Tagclass,这是一个基于增量解析的工具,可以将标签与其相应的族、行为和平台类关联起来。tag将行为和平台标记分类为定位器,并通过引入和迭代以下两种算法来实现增量解析:1)位置优先搜索,使用定位器查找家族标记;2)共现优先搜索,根据家族标记查找新的定位器。在两个基准数据集上进行的实验表明,tagclass3的解析准确率分别提高了21%和28%,优于现有的方法。据我们所知,tagclass1是第一个标签类确定的恶意软件标签解析工具,这将为众包恶意软件注释的研究铺平道路。tagclassas已经发布到社区11https://github.com/crowdma/tagclass。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
TagClass: A Tool for Extracting Class-Determined Tags from Massive Malware Labels via Incremental Parsing
VirusTotal is widely used for malware annotation by providing malware labels from a large set of anti-malware engines. A long-standing challenge in using these inconsistent labels is extracting class-determined tags. In this paper, we present Tagclass,a tool based on incremental parsing to associate tags with their corresponding family, behavior, and platform classes. Tagclasstreats behavior and platform tags as locators and achieves incremental parsing by introducing and iterating the following two algorithms: 1) location first search, which hits family tags using locators, and 2) co-occurrence first search, which finds new locators by family tags. Experiments across two benchmark datasets indicate Tagclassoutperforms existing methods, improving the parsing accuracy by 21% and 28%, respectively. To the best of our knowledge, Tagclassis the first tag class-determined malware label parsing tool, which would pave the way for research on crowdsourcing malware annotation. Tagclasshas been released to the community 11https://github.com/crowdma/tagclass.
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