Lightweight Privacy and Security Computing for Blockchained Federated Learning in IoT-Reference-Cited by-同舟云学术

Lightweight Privacy and Security Computing for Blockchained Federated Learning in IoT

Published:2023-09-15 Issue:18 Volume:10 Page:16048-16060
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Fan Mochan¹^ORCID,Ji Kailai¹,Zhang Zhaofeng¹,Yu Hongfang¹^ORCID,Sun Gang²^ORCID

Affiliation:

1. School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China

2. School of Information and Communication Engineering and the Agile and Intelligent Computing Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China

Funder

Open Research Projects of Zhejiang Lab

Natural Science Foundation of Sichuan Province

Sichuan Province Selected Funding for Postdoctoral Research Projects

PCL Future Greater-Bay Area Network Facilities for Large-Scale Experiments and Applications

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/ielx7/6488907/10242177/10102683.pdf?arnumber=10102683

Reference42 articles.

1. Deepchain: Auditable and privacy-preserving deep learning with blockchain-based incentive;weng;IEEE Trans Dependable Secure Comput,2021

2. Identity-Based Encryption from the Weil Pairing

3. Public-Key Cryptosystems Based on Composite Degree Residuosity Classes

4. PerFED-GAN: Personalized Federated Learning via Generative Adversarial Networks

5. Trusted Execution Environment: What It is, and What It is Not

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