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20212025
most citedGroup privacy for personalized federated learning

12 citations · 49 across the 13 of their papers we have counts for

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Showing cs.CRShow all

5 papers · 1 filter

cs.CR2022

Impact of Sampling on Locally Differentially Private Data Collection

Sayan Biswas, Graham Cormode, Carsten Maple

With the recent bloom of data, there is a huge surge in threats against individuals' private information. Various techniques for optimizing privacy-preserving data analysis are at…

cs.CR2022★ 10 cited

PRIVIC: A privacy-preserving method for incremental collection of location data

Sayan Biswas, Catuscia Palamidessi

With recent advancements in technology, the threats of privacy violations of individuals' sensitive data are surging. Location data, in particular, have been shown to carry a subst…

cs.CR2022★ 8 cited

A privacy preserving querying mechanism with high utility for electric vehicles

Ugur Ilker Atmaca, Sayan Biswas, Carsten Maple +1

Electric vehicles (EVs) are gaining popularity due to the growing awareness for a sustainable future. However, since there are disproportionately fewer charging stations than EVs,…

cs.CR2022

Tight Differential Privacy Blanket for Shuffle Model

Sayan Biswas, Kangsoo Jung, Catuscia Palamidessi

With the recent bloom of focus on digital economy, the importance of personal data has seen a massive surge of late. Keeping pace with this trend, the model of data market is start…

cs.CR2022★ 2 cited

Tight Differential Privacy Guarantees for the Shuffle Model with -Randomized Response

Sayan Biswas, Kangsoo Jung, Catuscia Palamidessi

Most differentially private (DP) algorithms assume a central model in which a reliable third party inserts noise to queries made on datasets, or a local model where the users local…