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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No Grammar, No Problem: Towards Fuzzing the Linux Kernel...

Alexander Bulekov (Boston University), Bandan Das (Red Hat), Stefan Hajnoczi (Red Hat), Manuel Egele (Boston University)

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AdvCAPTCHA: Creating Usable and Secure Audio CAPTCHA with Adversarial...

Hao-Ping (Hank) Lee (Carnegie Mellon University), Wei-Lun Kao (National Taiwan University), Hung-Jui Wang (National Taiwan University), Ruei-Che Chang (University of Michigan), Yi-Hao Peng (Carnegie Mellon University), Fu-Yin Cherng (National Chung Cheng University), Shang-Tse Chen (National Taiwan University)

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Adopt a PET! An Exploration of PETs, Policy, and...

Masoumeh Shafieinejad (Vector Institute), Xi He (Vector Institute and Univesity of Waterloo), Bailey Kacsmar (Amii & University of Alberta)

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