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

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.

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Tianhao Wang (Purdue University), Milan Lopuhaä-Zwakenberg (Eindhoven University of Technology), Zitao Li (Purdue University), Boris Skoric (Eindhoven University of Technology), Ninghui Li (Purdue University)

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On Using Application-Layer Middlebox Protocols for Peeking Behind NAT...

Teemu Rytilahti (Ruhr University Bochum), Thorsten Holz (Ruhr University Bochum)

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Are You Going to Answer That? Measuring User Responses...

Imani N. Sherman (University of Florida), Jasmine D. Bowers (University of Florida), Keith McNamara Jr. (University of Florida), Juan E. Gilbert (University of Florida), Jaime Ruiz (University of Florida), Patrick Traynor (University of Florida)

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Runqing Yang (Zhejiang University), Shiqing Ma (Rutgers University), Haitao Xu (Arizona State University), Xiangyu Zhang (Purdue University), Yan Chen (Northwestern University)

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