GBMIA: Gradient-based Membership Inference Attack in Federated Learning-Reference-Cited by-同舟云学术

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GBMIA: Gradient-based Membership Inference Attack in Federated Learning

Published:2023-05-28 Issue: Volume: Page:
ISSN:
Container-title:ICC 2023 - IEEE International Conference on Communications
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Author:

Wang Xiaodong¹,Wang Naiyu¹,Wu Longfei²,Guan Zhitao¹,Du Xiaojiang³,Guizani Mohsen⁴

Affiliation:

1. School of Control and Computer Engineering, North China Electric Power University,China

2. Fayetteville State University,Department of Mathematics & Computer Science,Fayetteville,NC,USA

3. Stevens Institute of Technology,Department of Electrical and Computer Engineering,Hoboken,NJ,USA

4. Mohamed Bin Zayed University of Artificial Intelligence,Machine Learning Department,Abu Dhabi,UAE

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10278505/10278554/10279702.pdf?arnumber=10279702

Reference24 articles.

1. An incentive mechanism for data sharing based on blockchain with smart contracts

2. Scalable Multi-party Private Set-Intersection;hazay;Public-key Cryptography,2017

3. Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning

4. Game of Gradients: Mitigating Irrelevant Clients in Federated Learning

5. Systematizing genome privacy research: A privacy-e Membership Inference Attacks Against Recommender Systems nhancing technologies perspective;mittos;The 11th Privacy Enhancing Technologies Symposium (PETS),2019

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