Federated Analytics: A Survey

  • Elkordy A
  • Ezzeldin Y
  • Han S
  • et al.
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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.

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APA

Elkordy, A. R., Ezzeldin, Y. H., Han, S., Sharma, S., He, C., Mehrotra, S., & Avestimehr, S. (2023). Federated Analytics: A Survey. APSIPA Transactions on Signal and Information Processing, 12(1). https://doi.org/10.1561/116.00000063

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