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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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PowerBench Dataset – Part 3: Cyber Attacks on EVCS

Authors: Jacob, Roshni Anna; Uddin, Md. Joshem; Olojede, Damilola R; Coskunuzer, Baris; Zhang, Jie;

PowerBench Dataset – Part 3: Cyber Attacks on EVCS

Abstract

PowerBench: EVCS Cyber Attack Datasets for Power Distribution Networks This dataset is part of the PowerBench benchmark suite designed to support machine learning research in resilient and secure power distribution networks. It includes one out of the three types of cyberattacks modeled on IEEE 34-bus, 123-bus, and 8500-node test feeders: EVCS Attacks Adversarial manipulation of the charging behavior of grid-connected electric vehicle charging stations (EVCS). Suitable for learning-based intrusion detection and localization of compromised EVCSs. Each attack dataset contains .pkl simulation files, .gml grid topology, and scenario metadata. All simulations were generated using OpenDSS via OpenDSSDirect.py. Please refer to the included README.md for detailed task guidance and loading instructions.

Related Organizations
Keywords

Machine Learning, Cyber Attacks, Anomaly Detection, Power Systems, Graph Neural Networks, Smart Grid

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average