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Thousands of malicious applications targeting mobile devices, including thepopular Android platform, are created every day. A large number of thoseapplications are created by a small number of professional under-ground actors,however previous studies overlooked such information as a feature in detectingand classifying malware, and in attributing malware to creators. Guided by thisinsight, we propose a method to improve on the performance of Android malwaredetection by incorporating the creator's information as a feature and classifymalicious applications into similar groups. We developed a system thatimplements this method in practice. Our system enables fast detection ofmalware by using creator information such as serial number of certificate.Additionally, it analyzes malicious be-haviors and permissions to increasedetection accuracy. The system also can classify malware based on similarityscoring. Finally, we showed detection and classification performance with 98%and 90% accuracy respectively.

Detecting and Classifying Android Malware using Static Analysis along with Creator Information