Android platform has become a primary target for malware. In this paper we present SafeDroid, an open source distributed service to detect malicious apps on Android by combining static analysis and machine learning techniques. It is composed by three micro-services, working together, combining static analysis and machine learning techniques. SafeDroid has been designed as a user friendly service, providing detailed feedback in case of malware detection. The detection service is optimized to be lightweight and easily updated. The feature set on which the micro-service of detection relies on on has been selected and optimized in order to focus only on the most distinguishing characteristics of the Android apps. We present a prototype to show the effectiveness of the detection mechanism service and the feasibility of the approach.
|Title of host publication||Proceedings of the 9th IEEE International Conference on Service Oriented Computing and Applications (SOCA 2016)|
|Publication status||Published - 2016|
|Event||9th IEEE International Conference on Service Oriented Computing and Applications (SOCA 2016) - Macau, China|
Duration: 4 Nov 2016 → 6 Nov 2016
Conference number: 9
|Conference||9th IEEE International Conference on Service Oriented Computing and Applications (SOCA 2016)|
|Period||04/11/2016 → 06/11/2016|