Practical Private Aggregation in Federated Learning Against Inference Attack
Author:
Affiliation:
1. College of Information Science and Technology, Donghua University, Shanghai, China
2. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China
Funder
Open Foundation of State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing
Link
http://xplorestaging.ieee.org/ielx7/6488907/9997152/09866515.pdf?arnumber=9866515
Reference44 articles.
1. Efficient differentially private secure aggregation for federated learning via hardness of learning with errors;stevens;arXiv 2112 06872,2021
2. Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption;hardy;arXiv 1711 10677,2017
3. Privacy Preserving Machine Learning with Homomorphic Encryption and Federated Learning
4. A Utility-Aware General Framework With Quantifiable Privacy Preservation for Destination Prediction in LBSs
5. Fully Homomorphic Encryption from Ring-LWE and Security for Key Dependent Messages
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