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How to Make Private Distributed Cardinality Estimation Practical, and Get Differential Privacy for Free
[article]
2020
IACR Cryptology ePrint Archive
Secure computation is a promising privacy enhancing technology, but it is often not scalable enough for data intensive applications. On the other hand, the use of sketches has gained popularity in data mining, because sketches often give rise to highly efficient and scalable sub-linear algorithms. It is natural to ask: what if we put secure computation and sketches together? We investigated the question and the findings are interesting: we can get security, we can get scalability, and somewhat
dblp:journals/iacr/HuLLGWGLD20
fatcat:35wk2lx6hbgttph67bhwutkuxq