Privacy Leakage in Federated Home Applications Using Gradient Inversion Algorithms-Reference-Cited by-同舟云学术

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Privacy Leakage in Federated Home Applications Using Gradient Inversion Algorithms

Published:2024-03-25 Issue: Volume:1 Page:1-6
ISSN:
Container-title:2024 IEEE International Conference on Industrial Technology (ICIT)
language:
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Author:

Chen Wenzhi¹,Sun Hongjian¹,You Minglei²,Jiang Jing³

Affiliation:

1. Durham University,Department of Engineering,Durham,UK,DHI 3LE

2. University of Nottingham,Department of Electrical and Electronic Engineering,Nottingham,UK,NG8 IBB

3. Northumbria University,Department of Mathematics, Physics and Electrical Engineering,Newcastle upon Tyne,UK,NEI 8ST

Funder

Royal Society

European Space Agency

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10540646/10540608/10540758.pdf?arnumber=10540758

Reference19 articles.

1. Communication-efficient learning of deep networks from decentralized data;McMahan;Artifical intelligence and statistics,2017

2. An integrated federated learning algorithm for short-term load forecasting

3. A Secure Federated Learning Framework for Residential Short Term Load Forecasting

4. Securing IoT-Based Smart Healthcare Systems by Using Advanced Lightweight Privacy-Preserving Authentication Scheme

5. Accurate Action Recommendation for Smart Home via Two-Level Encoders and Commonsense Knowledge

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