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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SketchFeature: High-Quality Per-Flow Feature Extractor Towards Security-Aware Data Plane

Sian Kim (Ewha Womans University), Seyed Mohammad Mehdi Mirnajafizadeh (Wayne State University), Bara Kim (Korea University), Rhongho Jang (Wayne State University), DaeHun Nyang (Ewha Womans University)

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Mysticeti: Reaching the Latency Limits with Uncertified DAGs

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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TZ-DATASHIELD: Automated Data Protection for Embedded Systems via Data-Flow-Based...

Zelun Kong (University of Texas at Dallas), Minkyung Park (University of Texas at Dallas), Le Guan (University of Georgia), Ning Zhang (Washington University in St. Louis), Chung Hwan Kim (University of Texas at Dallas)

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