Malware Prediction And Classification For Android Applications Using Machine Learning Techniques

Numerous paid and open-source applications have been produced as a result of the increased use of Mobile phones. These programs enable users to perform a wide range of tasks, including as communicating, playing games, and carrying out financial and educational tasks. Malicious app growth has become a significant problem that is holding back the development of a healthy mobile ecosystem. According to recent studies, new dangerous Android apps are released every 10 seconds. Users of the Android operating system can download and install software from unreliable websites including file-sharing websites and third-party app stores. The issue of malware infiltration has become so serious and significant that, according to recent statistics, 98% of mobile malware targeted Android smart phones. In this project we using SVM, KNN and CNN algorithms.