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DataFunTalk
DataFunTalk
Dec 18, 2020 · Artificial Intelligence

Federated Learning and Secure Multi‑Party Computation: Concepts, Security Challenges, and Practical Solutions

This article explains the evolution of federated learning, contrasts Google’s cross‑device horizontal approach with China’s cross‑silo vertical implementations, analyzes their security vulnerabilities, and demonstrates how secure multi‑party computation—including differential privacy, secure aggregation, and secret‑sharing techniques—can address these challenges while highlighting performance trade‑offs.

Federated Learningcross-silodifferential privacy
0 likes · 18 min read
Federated Learning and Secure Multi‑Party Computation: Concepts, Security Challenges, and Practical Solutions
DataFunSummit
DataFunSummit
Dec 16, 2020 · Artificial Intelligence

Federated Learning vs Secure Multi‑Party Computation: Concepts, Challenges, and Alibaba’s Solutions

This article explains the fundamentals of federated learning and secure multi‑party computation, compares their security and performance trade‑offs, discusses the differences between Google’s cross‑device FL and China’s cross‑silo FL, and presents Alibaba’s recent advances and practical solutions for privacy‑preserving collaborative modeling.

Federated LearningInformation Securitycross-silo
0 likes · 18 min read
Federated Learning vs Secure Multi‑Party Computation: Concepts, Challenges, and Alibaba’s Solutions