000000318 001__ 318
000000318 005__ 20170420034040.0
000000318 037__ $$aLERSSE-RefConfPaper-2017-004
000000318 100__ $$aPrimal Wijesekera
000000318 245__ $$aThe Feasibility of Dynamically Granted Permissions: Aligning Mobile Privacy with User Preferences
000000318 260__ $$c2017-04-20
000000318 300__ $$a17
000000318 520__ $$aCurrent smartphone operating systems regulate application permissions by prompting users on an ask-on-first-use basis. Prior research has shown that this method is ineffective because it fails to account for context: the circumstances under which an application first requests access to data may be vastly different than the circumstances under which it subsequently requests access. We performed a longitudinal 131-person field study to analyze the contextuality behind user privacy decisions to regulate access to sensitive resources. We built a classifier to make privacy decisions on the user’s behalf by detecting when context has changed and, when necessary, inferring privacy preferences based on the user’s past decisions and behavior. Our goal is to automatically grant appropriate resource requests without further user intervention, deny inappropriate requests, and only prompt the user when the system is uncertain of the user’s preferences. We show that our approach can accurately predict users’ privacy decisions 96.8% of the time, which is a four-fold reduction in error rate compared to current systems.
000000318 700__ $$aArjun Baokar
000000318 700__ $$aLynn Tsai
000000318 700__ $$aJoel Reardon
000000318 700__ $$aSerge Egelman
000000318 700__ $$aDavid Wagner
000000318 700__ $$aKonstantin Beznosov
000000318 8560_ $$flersse-it@ece.ubc.ca
000000318 8564_ $$uhttp://lersse-dl.ece.ubc.ca/record/318/files/wijesekera_oakland2017.pdf
000000318 8564_ $$uhttp://lersse-dl.ece.ubc.ca/record/318/files/wijesekera_oakland2017.pdf?subformat=pdfa$$xpdfa
000000318 909C4 $$pP. Wijesekera, A. Baokar, L.Tsai, J. Reardon, S. Egelman, D. Wagner, K. Beznosov, “The Feasibility of Dynamically Granted Permissions: Aligning Mobile Privacy with User Preferences,” in IEEE Symposium on Security and Privacy (IEEE S&P), San-Jose, CA, May 2017, 17 pages.
000000318 980__ $$aRefConfPaper