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Privacy detection of a mobile application program
Privacy detection of a mobile application program
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机译:移动应用程序的隐私检测
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摘要
Privacy violation detection of a mobile application program is disclosed. Regular histories of the mobile application are mined. A call-graph representation of the mobile application program can be created and sequences of events of interest according to the platform specification of the mobile application can be collected. A plurality of learnable features are extracted from the regular histories. The plurality of learnable features are combined into a single feature vector which is fed into a machine-learning-based classification algorithm. Whether the mobile application program includes one or more permissions for accessing unauthorized privacy data of a mobile application user is determined based on a machine learning classification of the single feature vector. The collected sequences can be reduced into a plurality of feature vectors which can include at least one of a happens-before feature and a multiplicity of occurrences feature.
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