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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Will They Share? Predicting Location Sharing Behaviors of Smartphone...

Muhammad Irtaza Safi, Abhiditya Jha (University of Central Florida); Malak Eihab Aly (New York University); Xinru Page (Bentley University); Sameer Patil (Indiana University); Pamela Wisniewski (University of Central Florida)

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Semi-Automated Synthesis of Driving Rules

Diego Ortiz, Leilani Gilpin, Alvaro A. Cardenas (University of California, Santa Cruz)

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I Still Know What You Watched Last Sunday: Privacy...

Carlotta Tagliaro (TU Wien), Florian Hahn (University of Twente), Riccardo Sepe (Guess Europe Sagl), Alessio Aceti (Sababa Security SpA), Martina Lindorfer (TU Wien)

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podft: On Accelerating Dynamic Taint Analysis with Precise Path...

Zhiyou Tian (Xidian University), Cong Sun (Xidian University), Dongrui Zeng (Palo Alto Networks), Gang Tan (Pennsylvania State University)

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