GenoPPML – a framework for genomic privacy-preserving machine learning-Reference-Cited by-同舟云学术

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GenoPPML – a framework for genomic privacy-preserving machine learning

Published:2022-07 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 15th International Conference on Cloud Computing (CLOUD)
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Author:

Carpov Sergiu¹,Gama Nicolas¹,Georgieva Mariya¹,Jetchev Dimitar¹

Affiliation:

1. Inpher,Lausanne,Switzerland

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9860274/9860367/09860936.pdf?arnumber=9860936

Reference58 articles.

1. TFHE: Fast Fully Homomorphic Encryption Over the Torus

2. Faster Fully Homomorphic Encryption: Bootstrapping in Less Than 0.1 Seconds

3. Sublinear GMW-Style Compiler for MPC with Preprocessing

4. Efficient multiparty protocols using circuit randomization;beaver;Annual International Cryptology Conference,1991

5. Combining Secret Sharing and Garbled Circuits for Efficient Private IEEE 754 Floating-Point Computations

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