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.

View More Papers

JBomAudit: Assessing the Landscape, Compliance, and Security Implications of...

Yue Xiao (IBM Research), Dhilung Kirat (IBM Research), Douglas Lee Schales (IBM Research), Jiyong Jang (IBM Research), Luyi Xing (Indiana University Bloomington), Xiaojing Liao (Indiana University)

Read More

Sheep's Clothing, Wolf's Data: Detecting Server-Induced Client Vulnerabilities in...

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),…

Read More

Programmer's Perception of Sensitive Information in Code

Xinyao Ma, Ambarish Aniruddha Gurjar, Anesu Christopher Chaora, Tatiana R Ringenberg, L. Jean Camp (Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington)

Read More