Dimitrios Michael Manias
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The FALCON-C framework proposes a flow-based autoencoder approach to detect cyber anomalies and label malicious flows in connected vehicular networks, achieving high accuracy in identifying attacks on EVSE components.
This paper reviews the current state of cybersecurity for EV charging infrastructure, analyzing existing machine learning countermeasures and proposing future directions to overcome data limitations in intrusion detection systems.
Papers
FALCON-C: Flow-based Analysis and Labeling for Connected Vehicular Network Cybersecurity
The FALCON-C framework proposes a flow-based autoencoder approach to detect cyber anomalies and label malicious flows in connected vehicular networks, achieving high accuracy in identifying attacks on…