IMDEA Networks Institute Publications Repository

Beyond content analysis: Detecting targeted ads via distributed counting

Iordanou, Costas and Kourtellis, Nicolas and Carrascosa Amigo, Juan Miguel and Soriente, Claudio and Cuevas, Rubén and Laoutaris, Nikolaos (2019) Beyond content analysis: Detecting targeted ads via distributed counting. In: ACM CoNEXT, December 9-12, 2019, Orlando, FL.

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Abstract

Being able to check whether an online advertisement has been targeted is essential for resolving privacy controversies and implementing in practice data protection regulations like GDPR, CCPA, and COPPA. In this paper we describe the design, implementation, and deployment of an advertisement auditing system called eyeWnder that uses crowdsourcing to reveal in real time whether a display advertisement has been targeted or not. Crowdsourcing simplifies the detection of targeted advertising, but requires reporting to a central repository the impressions seen by different users, thereby jeopardising their privacy. We break this deadlock with a privacy preserving data sharing protocol that allows eyeWnder to compute global statistics required to detect targeting, while keeping the advertisements seen by individual users and their browsing history private. We conduct a simulation study to explore the effect of different parameters and a live validation to demonstrate the accuracy of our approach. Unlike previous solutions, eyeWnder can even detect indirect targeting, ie, marketing campaigns that promote a product or service whose description bears no semantic overlap with its targeted audience.

Item Type: Conference or Workshop Papers (Paper)
Subjects: UNSPECIFIED
Divisions: UNSPECIFIED
Depositing User: Nikolaos Laoutaris
Date Deposited: 10 Oct 2019 13:43
Last Modified: 10 Oct 2019 13:43
URI: http://eprints.networks.imdea.org/id/eprint/2056

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