Molly Zhuangtong Huang (University of Macau), Rui Jiang (University of Macau), Tanusree Sharma (Pennsylvania State University), Kanye Ye Wang (University of Macau)

In the rapidly evolving Web3 ecosystem, transparent auditing has emerged as a critical component for both applications and users. However, there is a significant gap in understanding how users perceive this new form of auditing and its implications for Web3 security. Utilizing a mixed-methods approach that incorporates a case study, user interviews, and social media data analysis, our study leverages a risk perception model to comprehensively explore Web3 users' perceptions regarding information accessibility, the role of auditing, and its influence on user behavior. Based on these extensive findings, we discuss how this open form of auditing is shaping the security of the Web3 ecosystem, identifying current challenges, and providing design implications.

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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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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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mmProcess: Phase-Based Speech Reconstruction from mmWave Radar

Hyeongjun Choi, Young Eun Kwon, Ji Won Yoon (Korea University)

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