Analysis and Classification of Android Malware using Machine Learning Algorithms
Neha Tarar, Shweta Gaur Sharma, Cettymalla Rama Krishna · 2018
Android is the most widely used mobile operating system in the world. There has been a tremendous increment in the availability of Android applications in the Android Market or other third-party markets. Based on the openness feature of the Android platform, there has also been a huge increase in Android malware. The rapidly developing malware is a serious problem and there is a need for detection of Android malware to protect the system. This demands effective and efficient methods for Android malware detection. This paper provides a detailed discussion on different machine learning based analysis methods used for the classification of Android malware applications. In this paper, Opcode-based Android malware analysis approach has been proposed. For the classification of Android malware applications several machine learning algorithms have been used. The obtained results conclude that an efficient and more accurate malware classification is done in our proposed approach where an accuracy of 99.5% is achieved with a 0.995 TPR.