Malware Detection in Android Apps

Android is the leading market in the world and we can easily say that it is one of the fast growing technologies which influence lots of users all over the world. But due to its popularity & huge crowd it became the main targeting center for the attacker. To solve this problem there are many methods being used such as Anti-virus to find the malware in the app which match the signature of the app with its signature stored in its database which is also bypassed by the attacker by using new tactics. There is a security check done by the play store to stop the uploading of malicious applications into it. But the truth is that there are a lot of malicious applications available in the Play Store even after the security check. We use machine learning to classify whether an application is benign or malware. The static analysis is mainly focused on the manifest.xml file of an Android application and the dynamic analysis will be based on the actions it will be triggering while running on a mobile device. Our approach is to design an app which is truly based on the tensor flow model. Huge collection of dataset is used to perform static analysis of an app. In order to detect malware in the app which is miserably loaded by the user in their smartphone from the external sources.