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.

View More Papers

Onion Franking: Abuse Reports for Mix-Based Private Messaging

Matthew Gregoire (University of North Carolina at Chapel Hill), Margaret Pierce (University of North Carolina at Chapel Hill), Saba Eskandarian (University of North Carolina at Chapel Hill)

Read More

What’s Done Is Not What’s Claimed: Detecting and Interpreting...

Chang Yue (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China), Kai Chen (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China), Zhixiu Guo (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China), Jun Dai, Xiaoyan Sun (Department of Computer Science, Worcester Polytechnic Institute), Yi Yang (Institute of Information Engineering, Chinese Academy…

Read More

MingledPie: A Cluster Mingling Approach for Mitigating Preference Profiling...

Cheng Zhang (Hunan University), Yang Xu (Hunan University), Jianghao Tan (Hunan University), Jiajie An (Hunan University), Wenqiang Jin (Hunan University)

Read More