Yuxi Wu (Georgia Institute of Technology and Northeastern University), Jacob Logas (Georgia Institute of Technology), Devansh Ponda (Georgia Institute of Technology), Julia Haines (Google), Jiaming Li (Google), Jeffrey Nichols (Apple), W. Keith Edwards (Georgia Institute of Technology), Sauvik Das (Carnegie Mellon University)

Users make hundreds of transactional permission decisions for smartphone applications, but these decisions persist beyond the context in which they were made. We hypothesized that user concern over permissions varies by context, e.g., that users might be more concerned about location permissions at home than work. To test our hypothesis, we ran a 44-participant, 4-week experience sampling study, asking users about their concern over specific application-permission pairs, plus their physical environment and context. We found distinguishable differences in participants’ concern about permissions across locations and activities, suggesting that users might benefit from more dynamic and contextually-aware approaches to permission decision-making. However, attempts to assist users in configuring these more complex permissions should be made with the aim to reduce concern and affective discomfort—not to normalize and perpetuate this discomfort by replicating prior decisions alone.

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Spatial-Domain Wireless Jamming with Reconfigurable Intelligent Surfaces

Philipp Mackensen (Ruhr University Bochum), Paul Staat (Max Planck Institute for Security and Privacy), Stefan Roth (Ruhr University Bochum), Aydin Sezgin (Ruhr University Bochum), Christof Paar (Max Planck Institute for Security and Privacy), Veelasha Moonsamy (Ruhr University Bochum)

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AdvCAPTCHA: Creating Usable and Secure Audio CAPTCHA with Adversarial...

Hao-Ping (Hank) Lee (Carnegie Mellon University), Wei-Lun Kao (National Taiwan University), Hung-Jui Wang (National Taiwan University), Ruei-Che Chang (University of Michigan), Yi-Hao Peng (Carnegie Mellon University), Fu-Yin Cherng (National Chung Cheng University), Shang-Tse Chen (National Taiwan University)

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A Key-Driven Framework for Identity-Preserving Face Anonymization

Miaomiao Wang (Shanghai University), Guang Hua (Singapore Institute of Technology), Sheng Li (Fudan University), Guorui Feng (Shanghai University)

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