Adaptive Differentially Quantized Subspace Perturbation (ADQSP): A Unified Framework for Privacy-Preserving Distributed Average Consensus-Reference-Cited by-同舟云学术

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Adaptive Differentially Quantized Subspace Perturbation (ADQSP): A Unified Framework for Privacy-Preserving Distributed Average Consensus

Published:2024 Issue: Volume:19 Page:1780-1793
ISSN:1556-6013
Container-title:IEEE Transactions on Information Forensics and Security
language:
Short-container-title:IEEE Trans.Inform.Forensic Secur.

Author:

Li Qiongxiu¹^ORCID,Gundersen Jaron Skovsted²,Lopuhaä-Zwakenberg Milan³^ORCID,Heusdens Richard⁴^ORCID

Affiliation:

1. Department of Computer Science, Tsinghua University, Beijing, China

2. Department of Electronic Systems, Aalborg University, Aalborg, Denmark

3. Department of Mathematics and Computer Science, University of Twente, Enschede, The Netherlands

4. Netherlands Defence Academy (NLDA), Den Helder, The Netherlands

Funder

European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie

ERC Consolidator

“Caesar”

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Safety, Risk, Reliability and Quality

Link

http://xplorestaging.ieee.org/ielx7/10206/10319981/10360869.pdf?arnumber=10360869

Reference47 articles.

1. Smartphone ownership and Internet usage continues to climb in emerging economies;Poushter;Pew Res. Center,2016

2. Consensus and Cooperation in Networked Multi-Agent Systems

3. On the complexity of decentralized decision making and detection problems

4. Federated Learning: Challenges, Methods, and Future Directions

5. Privacy-preserving distributed speech enhancement forwireless sensor networks by processing in the encrypted domain

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Distributed Optimisation With Linear Equality and Inequality Constraints Using PDMM;IEEE Transactions on Signal and Information Processing over Networks;2024

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