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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Why People Still Fall for Phishing Emails: An Empirical...

Asangi Jayatilaka (Centre for Research on Engineering Software Technologies (CREST), The University of Adelaide, School of Computing Technologies, RMIT University), Nalin Asanka Gamagedara Arachchilage (School of Computer Science, The University of Auckland), M. Ali Babar (Centre for Research on Engineering Software Technologies (CREST), The University of Adelaide)

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Him of Many Faces: Characterizing Billion-scale Adversarial and Benign...

Shujiang Wu (Johns Hopkins University), Pengfei Sun (F5, Inc.), Yao Zhao (F5, Inc.), Yinzhi Cao (Johns Hopkins University)

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Blaze: A Framework for Interprocedural Binary Analysis

Matthew Revelle, Matt Parker, Kevin Orr (Kudu Dynamics)

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