Malton: Towards On-Device Non-Invasive Mobile Malware Analysis for ART
Lei Xue, Yajin Zhou, Ting Chen, Xiapu Luo, Guofei Gu
摘要
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 Malton, a novel on-device non-invasive analysis platform for the new Android runtime (i.e., the ART runtime). As a dynamic analysis tool, Malton 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 Malton using real-world malware samples. The experimental results showed that Malton 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.
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- TaintART: A Practical Multi-level Information-Flow Tracking System for Android RunTimeMingshen Sun, Tao Wei, John C. S. LuiCCS 2016 · 被引用 188 次
- TriggerScope: Towards Detecting Logic Bombs in Android ApplicationsYanick Fratantonio, Antonio Bianchi, William K. Robertson, Engin Kirda 等S&P 2016 · 被引用 161 次
- Harvesting Runtime Values in Android Applications That Feature Anti-Analysis TechniquesSiegfried Rasthofer, Steven Arzt, Marc Miltenberger, Eric BoddenNDSS 2016 · 被引用 157 次
- Going Native: Using a Large-Scale Analysis of Android Apps to Create a Practical Native-Code Sandboxing PolicyVitor Monte Afonso, Paulo L. de Geus, Antonio Bianchi, Yanick Fratantonio 等NDSS 2016 · 被引用 119 次
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