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| Content Provider | ACM Digital Library |
|---|---|
| Author | Yin, Heng Zhou, Rundong Henderson, Andrew Hu, Xunchao Wang, Xujiewen Prakash, Aravind Yan, Lok Kwong |
| Abstract | Dynamic binary analysis is a prevalent and indispensable technique in program analysis. While several dynamic binary analysis tools and frameworks have been proposed, all suffer from one or more of: prohibitive performance degradation, semantic gap between the analysis code and the program being analyzed, architecture/OS specificity, being user-mode only, lacking APIs, etc. We present DECAF, a virtual machine based, multi-target, whole-system dynamic binary analysis framework built on top of QEMU. DECAF provides Just-In-Time Virtual Machine Introspection combined with a novel TCG instruction-level tainting at bit granularity, backed by a plugin based, simple-to-use event driven programming interface. DECAF exercises fine control over the TCG instructions to accomplish on-the-fly optimizations. We present 3 platform-neutral plugins - Instruction Tracer, Keylogger Detector, and API Tracer, to demonstrate the ease of use and effectiveness of DECAF in writing cross-platform and system-wide analysis tools. Implementation of DECAF consists of 9550 lines of C++ code and 10270 lines of C code and we evaluate DECAF using CPU2006 SPEC benchmarks and show average overhead of 605% for system wide tainting and 12% for VMI. . |
| Starting Page | 248 |
| Ending Page | 258 |
| Page Count | 11 |
| File Format | |
| ISBN | 9781450326452 |
| DOI | 10.1145/2610384.2610407 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2014-07-21 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Dynamic binary analysis Virtual machine introspection Dynamic taint analysis |
| Content Type | Text |
| Resource Type | Article |
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