PROV-FL: Privacy-preserving Round Optimal Verifiable Federated Learning-Reference-Cited by-同舟云学术

PROV-FL: Privacy-preserving Round Optimal Verifiable Federated Learning

Published:2022-11-07 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 15th ACM Workshop on Artificial Intelligence and Security
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Author:

Dasu Vishnu Asutosh¹,Sarkar Sumanta²,Mandal Kalikinkar³

Affiliation:

1. The Pennsylvania State University, State College, PA, USA

2. University of Warwick, Coventry, United Kingdom

3. University of New Brunswick, Fredericton, Canada

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3560830.3563729

Reference41 articles.

1. Deep Learning with Differential Privacy

2. Michel Abdalla , Dario Catalano , Dario Fiore , Romain Gay , and Bogdan Ursu . 2018. Multi-Input Functional Encryption for Inner Products: Function-Hiding Realizations and Constructions Without Pairings . In Advances in Cryptology -- CRYPTO 2019 , , Hovav Shacham and Alexandra Boldyreva (Eds.). Springer International Publishing , Cham, 597--627. Michel Abdalla, Dario Catalano, Dario Fiore, Romain Gay, and Bogdan Ursu. 2018. Multi-Input Functional Encryption for Inner Products: Function-Hiding Realizations and Constructions Without Pairings. In Advances in Cryptology -- CRYPTO 2019, , Hovav Shacham and Alexandra Boldyreva (Eds.). Springer International Publishing, Cham, 597--627.

3. QUOTIENT

4. Charm: a framework for rapidly prototyping cryptosystems

5. Secure Single-Server Aggregation with (Poly)Logarithmic Overhead

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