Abu-Nassar et al., 2024
| Publication | Publication Date | Title |
|---|---|---|
| James et al. | Online false data injection attack detection with wavelet transform and deep neural networks | |
| Wu et al. | Extreme learning machine-based state reconstruction for automatic attack filtering in cyber physical power system | |
| Zhou et al. | Cyber-attack classification in smart grid via deep neural network | |
| Sakhnini et al. | Physical layer attack identification and localization in cyber–physical grid: An ensemble deep learning based approach | |
| Singh et al. | End-user privacy protection scheme from cyber intrusion in smart grid advanced metering infrastructure | |
| Abu-Nassar et al. | Early detection of cyber-physical attacks on electric vehicles fast charging stations using wavelets and deep learning | |
| Warraich et al. | Early detection of cyber–physical attacks on fast charging stations using machine learning considering vehicle-to-grid operation in microgrids | |
| Wu et al. | A genetic-algorithm support vector machine and DS evidence theory based fault diagnostic model for transmission line | |
| Najafzadeh et al. | Fault detection, classification and localization along the power grid line using optimized machine learning algorithms | |
| Qu et al. | Active and passive hybrid detection method for power CPS false data injection attacks with improved AKF and GRU‐CNN | |
| Li et al. | A hybrid machine learning framework for enhancing PMU-based event identification with limited labels | |
| Raghuvamsi et al. | Detection and reconstruction of measurements against false data injection and DoS attacks in distribution system state estimation: A deep learning approach | |
| Javaid et al. | RFE based feature selection and KNNOR based data balancing for electricity theft detection using BiLSTM-LogitBoost stacking ensemble model | |
| Zhu et al. | Robust representation learning for power system short-term voltage stability assessment under diverse data loss conditions | |
| Ren et al. | A universal defense strategy for data-driven power system stability assessment models under adversarial examples | |
| Kern et al. | Detection of anomalies in electric vehicle charging sessions | |
| Khan et al. | LSTM-based approach to detect cyber attacks on market-based congestion management methods | |
| Nassar et al. | A fast and effective automated wavelet-deep learning-based method to detect cyberattacks in microgrids with ev fast charging stations | |
| Lian et al. | Critical meter identification and network embedding based attack detection for power systems against false data injection attacks | |
| Jeyaraj et al. | Deep-block network for cyberattack mitigation and assessment in smart grid power system with resilience indices | |
| Narang et al. | Detection of cyber-attacks in smart power transmission system using mathematical morphology and autoencoder | |
| Warraich | Early detection of cyber-physical attacks in electric vehicles fast charging stations using machine learning | |
| Ebrahimi et al. | A Hidden Surveillant Transmission Line Protection Layer for Cyber-Attack Resilience of Power Systems | |
| Eldahshan et al. | A new theft detection approach for cyberattacks in PV generation | |
| Yao et al. | A Hybrid Data-Driven and Model-Based Anomaly Detection Scheme for DER Operation |