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Feature set selection in data mining techniques for unknown virus detection

机译:数据挖掘技术中用于未知病毒检测的功能集选择

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Detecting unknown viruses is a challenging research topic. Data mining approaches have been used to detect unknown viruses. The key to data mining lies on the feature set to be used. There are several different approaches have been tried before, simple heuristics, static features and dynamic features. In this paper, we present several different data mining approaches and compare the result of these approaches.
机译:检测未知病毒是一项具有挑战性的研究课题。数据挖掘方法已用于检测未知病毒。数据挖掘的关键在于要使用的功能集。以前尝试过几种不同的方法,包括简单的启发式,静态功能和动态功能。在本文中,我们提出了几种不同的数据挖掘方法,并比较了这些方法的结果。

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