DMSA-FL: secure and robust federated learning via double-masked secure aggregation with multiparty homomorphic encryption

This publication has 32 references indexed in Scilit:

• On the security and privacy of federated learning: A survey with attacks, defenses, frameworks, applications, and future directions
  Information Fusion, 2026
• Federated multi-agent reinforcement learning: A comprehensive survey of methods, applications and challenges
  Expert Systems with Applications, 2025
• HalfFedLearn: A secure federated learning with local data partitioning and homomorphic encryption
  Future Generation Computer Systems, 2025
• Federated learning enabled multi-key homomorphic encryption
  Expert Systems with Applications, 2024
• Privacy preserving verifiable federated learning scheme using blockchain and homomorphic encryption
  Applied Soft Computing, 2024
• PPFLHE: A privacy-preserving federated learning scheme with homomorphic encryption for healthcare data
  Applied Soft Computing, 2023
• A efficient and robust privacy-preserving framework for cross-device federated learning
  Complex & Intelligent Systems, 2023
• Privacy‐preserving federated learning based on multi‐key homomorphic encryption
  International Journal of Intelligent Systems, 2022
• Key Homomorphic PRFs and Their Applications
  2013
• Differential Privacy
  2006