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摘要: Android security has been built upon a permission-based mechanism which restricts accesses of third-party applications to critical resources on an device. The user must accept the set permissions application requires, before proceeding installation. This process aims inform users risk installing and using their device; but most often, even when permission system is well understood, are not aware enough threat endangered, trust either store or popularity application, installation without trying analyse intentions developer. Increasingly, one develops approaches aiming characterise malware with permissions, individually associatively, machine learning classifiers. objective in this paper investigate literature mechanisms for characterisation detection based previous aspects. For that, we illustrate describe limitations existing works promising considerations future research.