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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Statically Discover Cross-Entry Use-After-Free Vulnerabilities in the Linux Kernel

Hang Zhang (Indiana University Bloomington), Jangha Kim (The Affiliated Institute of ETRI, ROK), Chuhong Yuan (Georgia Institute of Technology), Zhiyun Qian (University of California, Riverside), Taesoo Kim (Georgia Institute of Technology)

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Binary Analysis: An AI Success Story

Perri Adams, Dartmouth College ISTS Fellow & John Hopkins SAIS Adjunct Professor

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Similarity Metric Method for Binary Basic Blocks of Cross-Instruction...

Xiaochuan Zhang (Artificial Intelligence Research Center, National Innovation Institute of Defense Technology), Wenjie Sun (State Key Laboratory of Mathematical Engineering and Advanced Computing), Jianmin Pang (State Key Laboratory of Mathematical Engineering and Advanced Computing), Fudong Liu (State Key Laboratory of Mathematical Engineering and Advanced Computing), Zhen Ma (State Key Laboratory of Mathematical Engineering and Advanced…

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