An Efficient and Secure Privacy-Preserving Federated Learning Framework Based on Multiplicative Double Privacy Masking
Source abstract
Abstract
With the increasing awareness of privacy protection and the improvement of relevant laws, federal learning has gradually become a new choice for cross-agency and cross-device machine learning. In order to solve the problems o... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Privacy-Preserving Technologies in Data · Cryptography and Data Security · Stochastic Gradient Optimization Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (38)
Show source-provided references
1. Deep learning: Applications, architectures, models, tools, and frameworks: A comprehensive survey10.1049/cit2.12180 ↗
2. A review on methods and applications in multimodal deep learning10.1145/3545572 ↗
3. A survey of privacy attacks in machine learning10.1145/3624010 ↗
4. PPML-Omics: A privacy-preserving federated machine learning method protects patients’ privacy in omic data
5. Preserving data privacy in machine learning systems10.1016/j.cose.2023.103605 ↗
6. Cross-silo federated learning for multi-tier networks with vertical and horizontal data partitioning10.1145/3543433 ↗
7. A survey on federated learning10.1016/j.knosys.2021.106775 ↗
8. J. Konečn, H. B. McMahan, F. X. Yu, P. Richtrik, A. T. Suresh and D. Bacon, “Federated learning: Strategies for improving communication efficiency,” 2016, arXiv:161005492.
9. McMahan · Artif. Intell. Statistics, PMLR · 2017 · 1273
10. A robust privacy-preserving federated learning model against model poisoning attacks10.1109/TIFS.2024.3420126 ↗
11. Federated learning with privacy-preserving and model IP-right-protection10.1007/s11633-022-1343-2 ↗
12. Privacy-preserving and communication-efficient energy prediction scheme based on federated learning for smart grids10.1109/JIOT.2022.3230586 ↗
13. Decentralized P2P federated learning for privacy-preserving and resilient mobile robotic systems10.1109/MWC.004.2200381 ↗
14. Multi-source data privacy protectionmethod based on homomorphic encryption and blockchain
15. Privacy-preserving and traceable federated learning for data sharing in industrial IoT applications10.1016/j.eswa.2022.119036 ↗
16. A privacy preserving framework for federated learning in smart healthcare systems
17. Eppda: An efficient privacy-preserving data aggregation federated learning scheme10.1109/TNSE.2022.3153519 ↗
18. Federated quantum-based privacy-preserving threat detection model for consumer internet of things
19. Privacy-preserving federated learning based on multi-key homomorphic encryption10.1002/int.22818 ↗
20. Homomorphic encryption-based privacy-preserving federated learning in iot-enabled healthcare system10.1109/TNSE.2022.3185327 ↗
21. Preserving privacy and security in federated learning
22. A survey on homomorphic encryption schemes: Theory and implementation10.1145/3214303 ↗
23. How to share a secret10.1145/359168.359176 ↗
24. A distributed synchronous SGD algorithm with global top-k sparsification for low bandwidth networks
25. Secure comparison protocols in the semi-honest model10.1109/JSTSP.2015.2429117 ↗
26. Practical secure aggregation for privacy-preserving machine learning
27. J. Daemen and V. Rijmen, “AES proposal: Rijndael,” 1999. Accessed: August 5, 2024. https://www.cs.miami.edu/home/burt/learning/Csc688.012/rijndael/rijndael_doc_V2.pdf
28. Paillier · Advances in Cryptology—EUROCRYPT’99 · 1999 · 1592 · 223
29. D. P. Kingma and J. Ba, “Adam: A method for stochastic optimization,” 2014, arXiv:14126980.
30. PEPFL: A framework for a practical and efficient privacy-preserving federated learning10.1016/j.dcan.2022.05.019 ↗
31. Privacy enhanced federated learning via privacy masks and additive homomorphic encryption
32. Vision models are more robust and fair when pretrained on uncurated images without supervision
33. Privacy-preserving federated deep learning with irregular users
34. A security-enhanced federated learning scheme based on homomorphic encryption and secret sharing10.3390/math12131993 ↗
35. A privacy-preserving federated learning scheme against poisoning attacks in smart grid10.1109/JIOT.2024.3365142 ↗
36. Gradient-based learning applied to document recognition10.1109/5.726791 ↗
37. MASKCRYPT: Federated learning with selective homomorphic encryption
38. Privacy preserving on updated parameters in federated learning