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.
CITATION STYLE
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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