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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TextBugger: Generating Adversarial Text Against Real-world Applications

Jinfeng Li (Zhejiang University), Shouling Ji (Zhejiang University), Tianyu Du (Zhejiang University), Bo Li (University of California, Berkeley), Ting Wang (Lehigh University)

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Geo-locating Drivers: A Study of Sensitive Data Leakage in...

Qingchuan Zhao (The Ohio State University), Chaoshun Zuo (The Ohio State University), Giancarlo Pellegrino (CISPA, Saarland University; Stanford University), Zhiqiang Lin (The Ohio State University)

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Vault: Fast Bootstrapping for the Algorand Cryptocurrency

Derek Leung (MIT CSAIL), Adam Suhl (MIT CSAIL), Yossi Gilad (MIT CSAIL), Nickolai Zeldovich (MIT CSAIL)

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