This page was created by Manish Tyagi. 

Freedman Fellowship 2023

Designing a Distributed, Privacy-Preserving Analytics Architecture with Personal Clouds

Department - Department of Computer and Data Sciences
Participant - Ryan Tatton

Mentions
https://scalar.case.edu/freedman-fellows/tatton-2021-2022
https://thedaily.case.edu/meet-the-winners-of-the-2021-2022-walter-freedman-and-karen-harrison-freedman-student-fellowships/

This project aims to address the privacy concerns of increasingly personalized modern applications that derive insight from user data. Specifically, he aims to develop a general distributed message-passing solution that allows for implementations of specific federated learning and otherwise distributed algorithms. Once the architecture is implemented, the privacy guarantees, scalability, and efficiency will be studied with various algorithms and threat models.


 

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