Chloe Fortuna (STR), JT Paasch (STR), Sam Lasser (Draper), Philip Zucker (Draper), Chris Casinghino (Jane Street), Cody Roux (AWS)

Modifying a binary program without access to the original source code is an error-prone task. In many cases, the modified binary must be tested or otherwise validated to ensure that the change had its intended effect and no others—a process that can be labor-intensive. This paper presents CBAT, an automated tool for verifying the correctness of binary transformations. CBAT’s approach to this task is based on a differential program analysis that checks a relative correctness property over the original and modified versions of a function. CBAT applies this analysis to the binary domain by implementing it as an extension to the BAP binary analysis toolkit. We highlight several features of CBAT that contribute to the tool’s efficiency and to the interpretability of its output. We evaluate CBAT’s performance by using the tool to verify modifications to three collections of functions taken from real-world binaries.

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Ryan Pickren (Georgia Institute of Technology), Tohid Shekari (Georgia Institute of Technology), Saman Zonouz (Georgia Institute of Technology), Raheem Beyah (Georgia Institute of Technology)

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Peizhuo Lv (Institute of Information Engineering, Chinese Academy of Sciences, China; School of Cyber Security, University of Chinese Academy of Sciences, China), Pan Li (Institute of Information Engineering, Chinese Academy of Sciences, China; School of Cyber Security, University of Chinese Academy of Sciences, China), Shenchen Zhu (Institute of Information Engineering, Chinese Academy of Sciences, China;…

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Chaoxiang He (Huazhong University of Science and Technology), Xiaojing Ma (Huazhong University of Science and Technology), Bin B. Zhu (Microsoft Research), Yimiao Zeng (Huazhong University of Science and Technology), Hanqing Hu (Huazhong University of Science and Technology), Xiaofan Bai (Huazhong University of Science and Technology), Hai Jin (Huazhong University of Science and Technology), Dongmei Zhang…

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Timing Channels in Adaptive Neural Networks

Ayomide Akinsanya (Stevens Institute of Technology), Tegan Brennan (Stevens Institute of Technology)

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