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A Quantitative Information Flow Analysis of the Topics API
We analyze the re-identification risk for individual Internet users introduced by the Topics API from the perspective of Quantitative Information Flow (QIF), an information- and decision-theoretic framework. Our model allows a theoretical analysis of both privacy and utility aspects of the API and their trade-off, and we show that the Topics API does have better privacy than third-party cookies. We leave the utility analyses for future work.
Mário S. Alvim
,
Natasha Fernandes
,
Annabelle McIver
,
Gabriel H. Nunes
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