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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Query Privacy in Data Spaces

Shuwen Liu (School of Data Science, The Chinese University of Hong Kong, Shenzhen, China), George C. Polyzos (School of Data Science, The Chinese University of Hong Kong, Shenzhen, China and ExcID P.C., Athens, Greece)

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SNITCH: Leveraging IP Geolocation for Active VPN Detection

Tomer Schwartz (Data and Security Laboratory Fujitsu Research of Europe Ltd), Ofir Manor (Data and Security Laboratory Fujitsu Research of Europe Ltd), Andikan Otung (Data and Security Laboratory Fujitsu Research of Europe Ltd)

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PBP: Post-training Backdoor Purification for Malware Classifiers

Dung Thuy Nguyen (Vanderbilt University), Ngoc N. Tran (Vanderbilt University), Taylor T. Johnson (Vanderbilt University), Kevin Leach (Vanderbilt University)

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