Smartphones and mobile devices are rapidly be- coming indispensable devices for many users. Unfortunately, they also become fertile grounds for hackers to deploy mal- ware. There is an urgent need to have a “security analytic & forensic system” which can facilitate analysts to examine, dissect, associate and correlate large number of mobile ap- plications. An effective analytic system needs to address the following questions: How to automatically collect and manage a high volume of mobile malware? How to analyze a zero- day suspicious application, and compare or associate it with existing malware families in the database? How to reveal similar malicious logic in various malware, and to quickly identify the new malicious code segment? In this paper, we present the design and implementation of DroidAnalytics, a signature based analytic system to automatically collect, manage, analyze and extract android malware. The system facilitates analysts to retrieve, associate and reveal malicious logics at the “opcode level”. We demonstrate the efficacy of DroidAnalytics using 150,368 Android applications, and successfully determine 2,494 Android malware from 102 different families, with 342 of them being zero-day malware samples from six different families. To the best of our knowledge, this is the first reported case in showing such a large Android malware analysis/detection. The evaluation shows the DroidAnalytics is a valuable tool and is effective in analyzing malware repackaging and mutations.
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DroidAnalytics is developed by Advanced Network and System Research Laboratory in the Department of Computer Science and Engineering at the Chinese University of Hong Kong (CUHK).Faculty: