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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OBI: a multi-path oblivious RAM for forward-and-backward-secure searchable encryption

Zhiqiang Wu (Changsha University of Science and Technology), Rui Li (Dongguan University of Technology)

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Non-Interactive Privacy-Preserving Sybil-Free Authentication Scheme in VANETs

Mahdi Akil (Karlstad University), Leonardo Martucci (Karlstad University), Jaap-Henk Hoepman (Radboud University)

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WIP: Augmenting Vehicle Safety With Passive BLE

Noah T. Curran (University of Michigan), Kang G. Shin (University of Michigan), William Hass (Lear Corporation), Lars Wolleschensky (Lear Corporation), Rekha Singoria (Lear Corporation), Isaac Snellgrove (Lear Corporation), Ran Tao (Lear Corporation)

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BlockScope: Detecting and Investigating Propagated Vulnerabilities in Forked Blockchain...

Xiao Yi (The Chinese University of Hong Kong), Yuzhou Fang (The Chinese University of Hong Kong), Daoyuan Wu (The Chinese University of Hong Kong), Lingxiao Jiang (Singapore Management University)

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