Youngwook Do (JPMorganChase and Georgia Institute of Technology), Tingyu Cheng (Georgia Institute of Technology and University of Notre Dame), Yuxi Wu (Georgia Institute of Technology and Northeastern University), HyunJoo Oh(Georgia Institute of Technology), Daniel J. Wilson (Northeastern University), Gregory D. Abowd (Northeastern University), Sauvik Das (Carnegie Mellon University)

Passive RFID is ubiquitous for key use-cases that include authentication, contactless payment, and location tracking. Yet, RFID chips can be read without users’ knowledge and consent, causing security and privacy concerns that reduce trust. To improve trust, we employed physically-intuitive design principles to create On-demand RFID (ORFID). ORFID’s antenna, disconnected by default, can only be re-connected by a user pressing and holding the tag. When the user lets go, the antenna automatically disconnects. ORFID helps users visibly examine the antenna’s connection: by pressing a liquid well, users can observe themselves pushing out a dyed, conductive liquid to fill the void between the antenna’s two bisected ends; by releasing their hold, they can see the liquid recede. A controlled evaluation with 17 participants showed that users trusted ORFID significantly more than a commodity RFID tag, both with and without an RFID-blocking wallet. Users attributed this increased trust to visible state inspection and intentional activation.

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THEMIS: Regulating Textual Inversion for Personalized Concept Censorship

Yutong Wu (Nanyang Technological University), Jie Zhang (Centre for Frontier AI Research, Agency for Science, Technology and Research (A*STAR), Singapore), Florian Kerschbaum (University of Waterloo), Tianwei Zhang (Nanyang Technological University)

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Automated Expansion of Privacy Data Taxonomy for Compliant Data...

Yue Qin (Indiana University Bloomington & Central University of Finance and Economics), Yue Xiao (Indiana University Bloomington & IBM Research), Xiaojing Liao (Indiana University Bloomington)

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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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