A Secure Federated Learning Framework using Blockchain and Differential Privacy-Reference-Cited by-同舟云学术

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A Secure Federated Learning Framework using Blockchain and Differential Privacy

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 9th International Conference on Cyber Security and Cloud Computing (CSCloud)/2022 IEEE 8th International Conference on Edge Computing and Scalable Cloud (EdgeCom)
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Author:

Firdaus Muhammad¹,Larasati Harashta Tatimma²,Rhee Kyung-Hyune³

Affiliation:

1. Pukyong National University,Department of Artificial Intelligence Convergence,Republic of Korea

2. Pusan National University,Department of Computer Engineering,Republic of Korea

3. Pukyong National University,Division of Computer Engineering,Republic of Korea

Funder

Ministry of Education

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9842862/9842867/09842971.pdf?arnumber=9842971

Reference26 articles.

1. Secure Data Sharing Through Untrusted Clouds with Blockchain-enhanced Key Management

2. Federated Learning for UAVs-Enabled Wireless Networks: Use Cases, Challenges, and Open Problems

3. DeepChain: Auditable and Privacy-Preserving Deep Learning with Blockchain-based Incentive

4. Federated learning for mobile keyboard prediction;hard,2018

5. On Blockchain-Enhanced Secure Data Storage and Sharing in Vehicular Edge Computing Networks

Cited by 8 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. Blockchain-Based Federated Learning for Data Privacy and Security;2024 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI);2024-05-09

2. Proof-of-authority-based secure and efficient aggregation with differential privacy for federated learning in industrial IoT;Internet of Things;2024-04

3. Privacy-Preserving Decentralized Biometric Identity Verification in Car-Sharing System;Journal of Multimedia Information System;2024-03-31

4. Comparative Analysis of Membership Inference Attacks in Federated and Centralized Learning;Information;2023-11-19

5. A Group Anonymity Based Federated Learning Framework;2023 International Conference on Digital Applications, Transformation & Economy (ICDATE);2023-07-14

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