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Cross-platform program analysis using machines learning based on universal features

机译:使用基于通用功能的机器学习进行跨平台程序分析

摘要

A method for performing program analysis includes receiving programs of a first platform that have been assigned a first label and programs of the first platform that have been assigned a second label. Each of the programs of the first platform is expressed as platform-independent logical features. A discriminatory model or classifier is trained, using machine learning, based on the expression of the programs of the first platform as platform-independent logical features, to distinguish between programs of the first label and programs of the second label. An unlabeled program of a second platform is received and is expressed as platform-independent logical features. The trained discriminatory model or classifier is used to determine if the unlabeled program warrants the first label or the second label, based on the expression of the unlabeled program as platform-independent logical features.
机译:一种用于执行程序分析的方法,包括:接收已经被分配了第一标签的第一平台的程序,以及已经被分配了第二标签的第一平台的程序。第一平台的每个程序都表示为平台无关的逻辑功能。基于第一平台的程序的表达作为与平台无关的逻辑特征,使用机器学习来训练区分模型或分类器,以区分第一标签的程序和第二标签的程序。接收第二平台的未标记程序,并将其表示为平台无关的逻辑特征。基于未标记程序作为平台独立的逻辑特征的表达,使用经过训练的判别模型或分类器来确定未标记程序是否需要第一标记或第二标记。

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