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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Fangming Gu (Institute of Information Engineering, Chinese Academy of Sciences), Qingli Guo (Institute of Information Engineering, Chinese Academy of Sciences), Jie Lu (Institute of Computing Technology, Chinese Academy of Sciences), Qinghe Xie (Institute of Information Engineering, Chinese Academy of Sciences), Beibei Zhao (Institute of Information Engineering, Chinese Academy of Sciences), Kangjie Lu (University of Minnesota),…

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SOK: An Evaluation of Quantum Authentication Through Systematic Literature...

Ritajit Majumdar (Indian Statistical Institute), Sanchari Das (University of Denver)

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Kushal Babel (Cornell Tech & IC3), Andrey Chursin (Mysten Labs), George Danezis (Mysten Labs & University College London (UCL)), Anastasios Kichidis (Mysten Labs), Lefteris Kokoris-Kogias (Mysten Labs & IST Austria), Arun Koshy (Mysten Labs), Alberto Sonnino (Mysten Labs & University College London (UCL)), Mingwei Tian (Mysten Labs)

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dAngr: Lifting Software Debugging to a Symbolic Level

Dairo de Ruck, Jef Jacobs, Jorn Lapon, Vincent Naessens (DistriNet, KU Leuven, 3001 Leuven, Belgium)

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