Muhammad Ahmad Bashir (Northeastern University), Umar Farooq (LUMS Pakistan), Maryam Shahid (LUMS Pakistan), Muhammad Fareed Zaffar (LUMS Pakistan), Christo Wilson (Northeastern University)

Widely reported privacy issues concerning major online advertising platforms (e.g., Facebook) have heightened concerns among users about the data that is collected about them. However, while we have a comprehensive understanding who collects data on users, as well as how tracking is implemented, there is still a significant gap in our understanding: what information do advertisers actually infer about users, and is this information accurate?

In this study, we leverage Ad Preference Managers (APMs) as a lens through which to address this gap. APMs are transparency tools offered by some advertising platforms that allow users to see the interest profiles that are constructed about them. We recruited 220 participants to install an IRB approved browser extension that collected their interest profiles from four APMs (Google, Facebook, Oracle BlueKai, and Neilsen eXelate), as well as behavioral and survey data. We use this data to analyze the size and correctness of interest profiles, compare their composition across the four platforms, and investigate the origins of the data underlying these profiles.

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Michael Rodler (University of Duisburg-Essen), Wenting Li (NEC Laboratories, Germany), Ghassan O. Karame (NEC Laboratories, Germany), Lucas Davi (University of Duisburg-Essen)

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Jaeho Lee (Rice University), Ang Chen (Rice University), Dan S. Wallach (Rice University)

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Michael Schwarz (Graz University of Technology), Florian Lackner (Graz University of Technology), Daniel Gruss (Graz University of Technology)

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Yangyong Zhang (Texas A&M University), Lei Xu (Texas A&M University), Abner Mendoza (Texas A&M University), Guangliang Yang (Texas A&M University), Phakpoom Chinprutthiwong (Texas A&M University), Guofei Gu (Texas A&M University)

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