Rachael Little, Dongpeng Xu (University of New Hampshire)

Software obfuscation is a form of code protection designed to hide the inner workings of a program from reverse engineering and analysis. Mixed Boolean Arithmetic (MBA) is one popular form that obscures simple arithmetic expressions via transformation to more complex equations involving both boolean and arithmetic operations. Most prior works focused on developing strong MBA at the source code or expression level; however, how many of them are resilient against compiler optimizations still remain unknown. In this work, we carefully inspect the strength of MBA obfuscation after various compiler optimizations. We embed MBA expressions from several popular datasets into C programs and examine how they appear post-compilation using the compilers GCC, Clang, and MSVC. Surprisingly, we discover a notable trend of reduction in MBA size and complexity after compiler optimization. We report our findings and discuss how MBA expressions are impacted by compiler optimizations.

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BitShield: Defending Against Bit-Flip Attacks on DNN Executables

Yanzuo Chen (The Hong Kong University of Science and Technology), Yuanyuan Yuan (The Hong Kong University of Science and Technology), Zhibo Liu (The Hong Kong University of Science and Technology), Sihang Hu (Huawei Technologies), Tianxiang Li (Huawei Technologies), Shuai Wang (The Hong Kong University of Science and Technology)

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B2R2: Building an Efficient Front-End for Binary Analysis

Minkyu Jung (KAIST), Soomin Kim (KAIST), HyungSeok Han (KAIST), Jaeseung Choi (KAIST), Sang Kil Cha (KAIST)

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I know what you MEME! Understanding and Detecting Harmful...

Yong Zhuang (Wuhan University), Keyan Guo (University at Buffalo), Juan Wang (Wuhan University), Yiheng Jing (Wuhan University), Xiaoyang Xu (Wuhan University), Wenzhe Yi (Wuhan University), Mengda Yang (Wuhan University), Bo Zhao (Wuhan University), Hongxin Hu (University at Buffalo)

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Can a Cybersecurity Question Answering Assistant Help Change User...

Lea Duesterwald (Carnegie Mellon University), Ian Yang (Carnegie Mellon University), Norman Sadeh (Carnegie Mellon University)

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