Name
Abstract | ||
|---|---|---|
It's an essential step to understand malware's behaviors for developing effective solutions. Though a number of systems have been proposed to analyze Android malware, they have been limited by incomplete view of inspection on a single layer. What's worse, various new techniques (e.g., packing, anti-emulator, etc.) employed by the latest malware samples further make these systems ineffective. In this paper, we propose maiton, a novel on-device non-invasive analysis platform for the new Android runtime (i.e., the ART runtime). As a dynamic analysis tool, maiton runs on real mobile devices and provides a comprehensive view of malware's behaviors by conducting multi-layer monitoring and information flow tracking, as well as efficient path exploration. We have carefully evaluated maiton using real-world malware samples. The experimental results showed that maiton is more effective than existing tools, with the capability to analyze sophisticated malware samples and provide a comprehensive view of malicious behaviors of these samples. |
Year | Venue | Field |
|---|---|---|
2017 | PROCEEDINGS OF THE 26TH USENIX SECURITY SYMPOSIUM (USENIX SECURITY '17) | Mobile malware,Computer security,Computer science |
DocType | Citations | PageRank |
Conference | 10 | 0.47 |
References | Authors | |
45 | 5 | |