000000321 001__ 321
000000321 005__ 20180214065342.0
000000321 037__ $$aLERSSE-RefConfPaper-2018-001
000000321 100__ $$aPrimal Wijesekera
000000321 245__ $$aContextualizing Privacy Decisions for Better Prediction (and Protection)
000000321 260__ $$c2018-02-08
000000321 300__ $$a12
000000321 520__ $$aModern mobile operating systems implement an ask-on-first-use policy to regulate applications’ access to private user data: the user is prompted to allow or deny access to a sensitive resource the first time an app attempts to use it. Prior research shows that this model may not adequately capture user privacy preferences because subsequent requests may occur under varying contexts. To address this shortcoming, we implemented a novel privacy management system in Android, in which we use contextual signals to build a classifier that predicts user privacy preferences under various scenarios. We performed a 37-person field study to evaluate this new permission model under normal device usage. From our exit interviews and collection of over 5 million data points from participants, we show that this new permission model reduces the error rate by 75% (i.e., fewer privacy violations), while preserving usability. We offer guidelines for how platforms can better support user privacy decision making.
000000321 6531_ $$aPrivacy
000000321 6531_ $$amobile permissions
000000321 6531_ $$aaccess control
000000321 6531_ $$auser study
000000321 700__ $$aJoel Reardon
000000321 700__ $$aIrwin Reyes
000000321 700__ $$aLynn Tsai
000000321 700__ $$aJung-Wei Chen
000000321 700__ $$aNathan Good
000000321 700__ $$aDavid Wagner
000000321 700__ $$aKonstantin Beznosov
000000321 700__ $$aSerge Egelman
000000321 8560_ $$fprimal@ece.ubc.ca
000000321 8564_ $$uhttp://lersse-dl.ece.ubc.ca/record/321/files/proceedings.pdf
000000321 8564_ $$uhttp://lersse-dl.ece.ubc.ca/record/321/files/proceedings.pdf?subformat=pdfa$$xpdfa
000000321 909C4 $$pPrimal Wijesekera, Joel Reardon, Irwin Reyes, Lynn Tsai, Jung-Wei Chen, Nathan Good, David Wagner, Konstantin Beznosov, and Serge Egelman. Contextualizing Privacy Decisions for Better Prediction (and Protection). Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’18), 2018.
000000321 980__ $$aRefConfPaper