Spatio-temporal data-driven detection of false data injection attacks in power distribution systems-Reference-Cited by-同舟云学术

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Spatio-temporal data-driven detection of false data injection attacks in power distribution systems

Published:2023-02 Issue: Volume:145 Page:108612
ISSN:0142-0615
Container-title:International Journal of Electrical Power & Energy Systems
language:en
Short-container-title:International Journal of Electrical Power & Energy Systems

Author:

Musleh Ahmed S.,Chen Guo^ORCID,Yang Dong Zhao,Wang Chen,Chen Shiping

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Reference31 articles.

1. Electricity Theft Detection in AMI Using Customers’ Consumption Patterns;Jokar;IEEE Trans Smart Grid,2016

2. History of Industrial Control System Cyber Incidents;Hemsley,2018

3. Evaluating Detectors on Optimal Attack Vectors That Enable Electricity Theft and DER Fraud;Krishna;IEEE J Sel Top Signal Process,2018

4. Vulnerabilities, Threats, and Impacts of False Data Injection Attacks in Smart Grids: An Overview;Musleh,2020

5. Review on cyber vulnerabilities of communication protocols in industrial control systems;Xu,2017

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1. A Unified Cyber Attack Detection and Mitigation Framework for an Islanded AC Microgrid;IEEE Transactions on Systems, Man, and Cybernetics: Systems;2024-09

2. Data-driven learning-based classification model for mitigating false data injection attacks on dynamic line rating systems;Sustainable Energy, Grids and Networks;2024-06

3. Novel cyber-physical collaborative detection and localization method against dynamic load altering attacks in smart energy grids;Global Energy Interconnection;2024-06

4. A robust distribution network state estimation method based on enhanced clustering Algorithm: Accounting for multiple DG output modes and data loss;International Journal of Electrical Power & Energy Systems;2024-06

5. Detection of False Data Injection Attacks on Smart Grids Based on A-BiTG Approach;Electronics;2024-05-15

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