Optimizing the Parameters of Pipelined Multi-Party Computation for Privacy-Preserving Machine Learning Applications
Author:
Affiliation:
1. Florida International University,Advanced Wireless and Security Lab,Miami,FL
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10622104/10622158/10623002.pdf?arnumber=10623002
Reference14 articles.
1. Machine Learning Operations (MLOps): Overview, Definition, and Architecture;Kreuzberger;IEEE Access,2023
2. Secure Multiparty Computation (MPC);Lindell,2020
3. Maliciously Secure Matrix Multiplication with Applications to Private Deep Learning
4. Deep Learning with Differential Privacy
5. Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware;Tramèr,2019
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