Florian Lachner, Minzhe Yuan Chen Cheng, Theodore Olsauskas-Warren (Google)

Online behavioral advertising is a double-edged sword. While relevant display ads are generally considered useful, opaque tracking based on third-party cookies has reached unfettered sprawl and is deemed to be privacy-intrusive. However, existing ways to preserve privacy do not sufficiently balance the needs of both users and the ecosystem. In this work, we evaluate alternative browser controls. We leverage the idea of inferring interests on users’ devices and designed novel browser controls to manage these interests. Through a mixed method approach, we studied how users feel about this approach. First, we conducted pilot interviews with 9 participants to test two design directions. Second, we ran a survey with 2,552 respondents to measure how our final design compares with current cookie settings. Respondents reported a significantly higher level of perceived privacy and feeling of control when introduced to the concept of locally inferred interests with an option for removal.

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FCGAT: Interpretable Malware Classification Method using Function Call Graph...

Minami Someya (Institute of Information Security), Yuhei Otsubo (National Police Academy), Akira Otsuka (Institute of Information Security)

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WIP: Infrared Laser Reflection Attack Against Traffic Sign Recognition...

Takami Sato (University of California, Irvine), Sri Hrushikesh Varma Bhupathiraju (University of Florida), Michael Clifford (Toyota InfoTech Labs), Takeshi Sugawara (The University of Electro-Communications), Qi Alfred Chen (University of California, Irvine), Sara Rampazzi (University of Florida)

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Analyzing the Patterns and Behavior of Users When Detecting...

Nick Ceccio, Naman Gupta, Majed Almansoori, Rahul Chatterjee (University of Wisconsin-Madison)

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