Euirim Choi, Claire Dolin, Aaron Goldman, Chang Min Hahn, Shawn Shan, Ben Weinshel, Michelle L. Mazurek, Blase Ur
Proceedings of the Thirteenth Symposium On Usable Privacy and Security (SOUPS). Santa Clara, CA, July 2017. (SOUPS 2017)
Distinguished Poster Award
Targeting advertisements to specific users based on their browsing activity can be helpful for both users and advertising networks, yet many users also find this practice unsettling and privacy-invasive. Although a number of privacy tools can help users control tracking, average users are left utterly confused about online behavioral advertising (OBA) even after using such tools. We are working to move beyond existing tools, which alert users to tracking occurring at the current moment, by designing and testing a tool that takes a data-driven, personalized approach to privacy awareness. We describe our work in progress designing a browser extension that enables users to explore what information third-party companies have tracked about them over time, as well as what those companies may have inferred about their interests from this data. We are currently exploring the impact of presenting different abstractions and granularities of the information tracked, as well as evaluating user reactions and concerns related to different methods of making inferences and targeting ads.