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FedEVCP: Federated Learning-Based Anomalies Detection for Electric Vehicle Charging Pile
The Computer Journal,
2024
DOI:10.1093/comjnl/bxad078
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[2]
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FedEVCP: Federated Learning-Based Anomalies Detection for Electric Vehicle Charging Pile
The Computer Journal,
2024
DOI:10.1093/comjnl/bxad078
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[3]
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Cybersecurity in the Transportation Industry
2024
DOI:10.1002/9781394204472.ch8
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[4]
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Smart EV-Hub: A Smart Development of an Internet of Things based Electric Vehicle Charging Station using Artificial Intelligence
2024 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI),
2024
DOI:10.1109/ACCAI61061.2024.10602038
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[5]
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Implementation and Test Bench Development of GB/T 27930-2015 Communication Protocol for Electric Vehicle Charger
IEEE Transactions on Industry Applications,
2024
DOI:10.1109/TIA.2024.3425570
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[6]
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A comprehensive survey of cyberattacks on EVs: Research domains, attacks, defensive mechanisms, and verification methods
Defence Technology,
2024
DOI:10.1016/j.dt.2024.06.009
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[7]
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FedEVCP: Federated Learning-Based Anomalies Detection for Electric Vehicle Charging Pile
The Computer Journal,
2023
DOI:10.1093/comjnl/bxad078
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[8]
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A Comprehensive Review of Cybersecurity in Inverter-Based Smart Power System Amid the Boom of Renewable Energy
IEEE Access,
2022
DOI:10.1109/ACCESS.2022.3163551
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[9]
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A Comprehensive Review of Cybersecurity in Inverter-Based Smart Power System Amid the Boom of Renewable Energy
IEEE Access,
2022
DOI:10.1109/ACCESS.2022.3163551
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[10]
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A Security Authentication Method between the Charging Pile and Battery Management System
2021 IEEE 4th International Conference on Electronics Technology (ICET),
2021
DOI:10.1109/ICET51757.2021.9450982
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[11]
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Test Method of Communication Protocol of Standard Group Components of Electric Vehicle Charging Equipment
Journal of Physics: Conference Series,
2021
DOI:10.1088/1742-6596/2066/1/012032
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[12]
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Key Security Challenges for Electric Vehicle Charging System
2020 2nd International Conference on Artificial Intelligence and Advanced Manufacture (AIAM),
2020
DOI:10.1109/AIAM50918.2020.00061
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