Privacy-Preserved Generative Network for Trustworthy Anomaly Detection in Smart Grids: A Federated Semisupervised Approach
Author:
Affiliation:
1. Faculty of computers and Informatics, Zagazig University, Zagazig, Egypt
2. School of Engineering and Information Technology, Australian Defence Force Academy, University of New South Wales, Kensington, NSW, Australia
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/9424/9944026/09754257.pdf?arnumber=9754257
Reference31 articles.
1. Federated optimization in heterogeneous networks;li,2018
2. Deep learning methods in network intrusion detection: A survey and an objective comparison
3. Intrusion Detection for Cyber–Physical Systems Using Generative Adversarial Networks in Fog Environment
4. Detecting False Data Injection Attacks in Smart Grids: A Semi-Supervised Deep Learning Approach
5. Adversarial Semi-Supervised Learning for Diagnosing Faults and Attacks in Power Grids
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