Caleb Helbling, Graham Leach-Krouse, Sam Lasser, Greg Sullivan (Draper)

This paper introduces cozy, a tool for analyzing and visualizing differences between two versions of a software binary. The primary use case for cozy is validating “micropatches”: small binary or assembly-level patches inserted into existing compiled binaries. To perform this task, cozy leverages the Python-based angr symbolic execution framework. Our tool analyzes the output of symbolic execution to find end states for the pre- and post-patched binaries that are compatible (reachable from the same input). The tool then compares compatible states for observable differences in registers, memory, and side effects. To aid in usability, cozy comes with a web-based visual interface for viewing comparison results. This interface provides a rich set of operations for pruning, filtering, and exploring different types of program data.

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Reinforcement Unlearning

Dayong Ye (University of Technology Sydney), Tianqing Zhu (City University of Macau), Congcong Zhu (City University of Macau), Derui Wang (CSIRO’s Data61), Kun Gao (University of Technology Sydney), Zewei Shi (CSIRO’s Data61), Sheng Shen (Torrens University Australia), Wanlei Zhou (City University of Macau), Minhui Xue (CSIRO's Data61)

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Vision: The Price Should Be Right: Exploring User Perspectives...

Jacob Hopkins (Texas A&M University - Corpus Christi), Carlos Rubio-Medrano (Texas A&M University - Corpus Christi), Cori Faklaris (University of North Carolina at Charlotte)

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Revisiting EM-based Estimation for Locally Differentially Private Protocols

Yutong Ye (Institute of software, Chinese Academy of Sciences & Zhongguancun Laboratory, Beijing, PR.China.), Tianhao Wang (University of Virginia), Min Zhang (Institute of Software, Chinese Academy of Sciences), Dengguo Feng (Institute of Software, Chinese Academy of Sciences)

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