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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The Vulnerabilities Less Exploited: Cyberattacks on End-of-Life Satellites

Frank Lee and Gregory Falco (Johns Hopkins University) Presenter: Frank Lee

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Folk Models of Misinformation on Social Media

Filipo Sharevski (DePaul University), Amy Devine (DePaul University), Emma Pieroni (DePaul University), Peter Jachim (DePaul University)

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CLExtract: Recovering Highly Corrupted DVB/GSE Satellite Stream with Contrastive...

Minghao Lin (University of Colorado Boulder), Minghao Cheng (Independent Researcher), Dongsheng Luo (Florida International University), Yueqi Chen (University of Colorado Boulder) Presenter: Minghao Lin

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