Abstract: - Android application security is based on a consent approach that limits access to important resources on an Android device by third-party Android apps. Before proceeding with the installation, the user must approve the set of rights that the programmer needs. This process aims to inform users of the risk of trying to install and using an implementation on their device; however, even when the permission system is well comprehended, users are often unaware of the threat posed, and instead trust the app store or the prominence of the app, and acknowledge the insertion without questioning the developer's motivations. Machine learning and Deep learning classifiers are increasingly being used to categories malware based on permissions, either separately or associatively. The goal of this research is to look at strategies for characterization and detection of malware in the literature based on the preceding elements. We do so by illustrating and describing the limits of previous research as well as potential future research topics.Keywords: Android applications, malware detection, permission-related APIs, random forests, software security