Kruminis, Edvinas and Navaie, Keivan and Ascigil, Onur (2025) BB-FLoC : A Blockchain-based Targeted Advertisement Scheme with K-Anonymity. ACM Distributed Ledger Technologies: 19. ISSN 2769-6480
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Abstract
New data protection regulations, e.g., General Data Protection Regulation (GDPR), enforced advertisement providers to amend their conventional approaches, enhancing users’ data privacy. As a result, major internet browsers, such as Apple Safari and Firefox, were quick to announce their plans to remove third-party cookies from their browsers entirely. In an effort to preserve conventional advertising practices, Google proposed a Federated Learning of Cohorts (FLoC) system to deliver higher privacy guarantees to users while also providing interest-based advertising. In FLoC, users sharing similar browsing histories are put into cohorts, and thus advertisements can be targeted to them as a group, rather than individually. Since each user independently calculates their cohort group, a minimum cohort size cannot be enforced, making them vulnerable to identification and tracking. To address this issue, in this article, a blockchain-based FLoC (BB-FLoC) system is proposed that guarantees k-anonymity for its users while at the same time allowing for effective personalised advertising. We further evaluate the operational feasibility of such a design and demonstrate that k-anonymity guarantees can be fulfilled in a fully decentralised manner in the proposed system. The proposed system is relatively lightweight, showcasing that it can be adapted for low-end devices, such as mobile phones.