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Graph-based malware classification based on file relationships

机译:基于文件关系的基于图的恶意软件分类

摘要

A reliable automated malware classification approach with substantially low false positive rates is provided. Graph-based local and/or global file relationships are used to improve malware classification along with a feature selection algorithm. File relationships such as containing, creating, copying, downloading, modifying, etc. are used to assign malware probabilities and simultaneously reduce the false positive and false negative rates on executable files.
机译:提供了一种可靠的自动化恶意软件分类方法,其误报率极低。基于图的本地和/或全局文件关系与功能选择算法一起用于改善恶意软件分类。文件关系(例如包含,创建,复制,下载,修改等)用于分配恶意软件概率,同时减少可执行文件的误报率和误报率。

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