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The number of malware applications targeting the Android operating system has significantly increased in recent years. Malicious applications pose a significant threat to Android platform security. We propose ANASTASIA, a system to detect malicious Android applications through statically analyzing applications' behaviors. ANASTASIA provides a more complete coverage of security behaviors when compared to state-of-the-art solutions. We utilize a large number of statically extracted features from various security behavioral characteristics of an application. We built a Machine Learning-based detection framework with high performance detection and acceptable false positive rate. The significance of our work is to develop a lightweight malware detection system for Android-powered smartphones that leverages robust, effective, and efficient features. Besides, in order to assess our solution, we used a reliable, large …