NDSS 2020 DeepBinDiff: Learning Program-Wide Code Representations for Binary Diffing

Описание: SESSION 7B-1 DeepBinDiff: Learning Program-Wide Code Representations for Binary Diffing

Binary diffing analysis quantitatively measures the differences between two given binaries and produces fine-grained basic block matching. It has been widely used to enable different kinds of critical security analysis. However, all existing program analysis and machine learning based techniques suffer from low accuracy, poor scalability, coarse granularity, or require extensive labeled training data to function. In this paper, we propose an unsupervised program-wide code representation learning technique to solve the problem. We rely on both the code semantic information and the program-wide control flow information to generate block embeddings. Furthermore, we propose a k-hop greedy matching algorithm to find the optimal diffing results using the generated block embeddings. We implement a prototype called DeepBinDiff and evaluate its effectiveness and efficiency with large number of binaries. The results show that our tool could outperform the state-of-the-art binary diffing tools by a large margin for both cross-version and cross-optimization level diffing. A case study for OpenSSL using real-world vulnerabilities further demonstrates the usefulness of our system.


PAPER
https://www.ndss-symposium.org/wp-con...

SLIDES


AUTHORS
Yue Duan (Cornell University)
Xuezixiang Li (UC Riverside)
Jinghan Wang (UC Riverside)
Heng Yin (UC Riverside)


Network and Distributed System Security (NDSS) Symposium 2020, 23-26 February 2019, Catamaran Resort Hotel & Spa in San Diego, California.
https://www.ndss-symposium.org/ndss-p...


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The Network and Distributed System Security Symposium (NDSS) fosters information exchange among researchers and practitioners of network and distributed system security. The target audience includes those interested in practical aspects of network and distributed system security, with a focus on actual system design and implementation. A major goal is to encourage and enable the Internet community to apply, deploy, and advance the state of available security technologies.
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