Federated Analytics: A Survey

Ahmed Roushdy Elkordy, Yahya H. Ezzeldin, Shanshan Han, Shantanu Sharma, Chaoyang He, Sharad Mehrotra, Salman Avestimehr

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Federated analytics (FA) is a privacy-preserving framework for computing data analytics over multiple remote parties (e.g., mobile devices) or silo-ed institutional entities (e.g., hospitals, banks) without sharing the data among parties. Motivated by the practical use cases of federated analytics, we follow a systematic discussion on federated analytics in this article. In particular, we discuss the unique characteristics of federated analytics and how it differs from federated learning. We also explore a wide range of FA queries and discuss various existing solutions and potential use case applications for different FA queries.

Original languageEnglish (US)
Article numbere4
JournalAPSIPA Transactions on Signal and Information Processing
Volume12
Issue number1
DOIs
StatePublished - 2023

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Information Systems

Keywords

  • Federated analytics
  • distributed computing
  • privacy

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