Privacy-Preserving and Communication-Efficient Energy Prediction Scheme Based on Federated Learning for Smart Grids-Reference-Cited by-同舟云学术

Privacy-Preserving and Communication-Efficient Energy Prediction Scheme Based on Federated Learning for Smart Grids

Published:2023-05-01 Issue:9 Volume:10 Page:7719-7736
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Badr Mahmoud M.¹,Mahmoud Mohamed M. E. A.²^ORCID,Fang Yuguang³^ORCID,Abdulaal Mohammed⁴^ORCID,Aljohani Abdulah Jeza⁴^ORCID,Alasmary Waleed⁵^ORCID,Ibrahem Mohamed I.¹^ORCID

Affiliation:

1. Department of Network and Computer Security: Cybersecurity, College of Engineering, SUNY Polytechnic Institute, Utica, NY, USA

2. Department of Electrical and Computer Engineering, Tennessee Technological University, Cookeville, TN, USA

3. Department of Computer Science, City University of Hong Kong, Hong Kong, SAR, China

4. Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah, Saudi Arabia

5. Department of Computer Engineering, Umm Al-Qura University, Mecca, Saudi Arabia

Funder

Makkah Digital Gate Initiative

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/ielx7/6488907/10106528/10005179.pdf?arnumber=10005179

Reference38 articles.

1. PMBFE: Efficient and Privacy-Preserving Monitoring and Billing Using Functional Encryption for AMI Networks

2. Evaluating Detectors on Optimal Attack Vectors That Enable Electricity Theft and DER Fraud

3. Deep Learning Detection of Electricity Theft Cyber-Attacks in Renewable Distributed Generation

4. Detection of False-Reading Attacks in Smart Grid Net-Metering System

5. Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network

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