Emerging Challenges in Smart Grid Cybersecurity Enhancement: A Review
Abstract
:1. Introduction
- The accuracy of cyber-attack detection and identification.
- Computational burden when detecting and identifying cyber-attacks.
- Robustness against various factors affecting cyber-attack detection and identification.
2. Fundamentals of Cyber-Attacks Detection and Identification in the Smart Grid
3. Cyber-Attack Detection and Identification Methods
3.1. Data-Driven Methods
3.2. State Estimation Methods
3.3. Other Methods
4. Comparison of Different Cyber-Attack Detection and Identification Techniques
5. Conclusions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Reference | Main Objective(s) | Proposed Method | Resilience Criteria | ||
---|---|---|---|---|---|
Accuracy | Computational Burden | Robustness against External Factors | |||
[10] | Malicious Meters Identification | Artificial Intelligence-Based Algorithm | ✓ | - | - |
[11] | Cyber-Attack Detection and Identification | Supervised Learning Algorithm | ✓ | - | - |
[12] | Online Cyber-Attack Identification | Reinforcement Learning-Based Algorithm | ✓ | ✓ | ✓ |
[13] | Cyber-Attack Detection | Multivariate Gaussian-Based Method | ✓ | - | - |
[14] | Cyber-Attack Detection | Isolation Forest PCA-Based Method | ✓ | ✓ | - |
[15] | Cyber-Attack Detection | Extremely Randomized Trees KPCA-Based Method | ✓ | ✓ | ✓ |
[16] | Cyber-Attack Detection | Isolation Forest Method | ✓ | - | ✓ |
[17] | Cyber-Attack Detection and Identification | Unsupervised Learning Algorithm | ✓ | - | ✓ |
[18] | Cyber-Attack Detection | Gaussian Markov Random Field Method | ✓ | ✓ | - |
[19] | Cyber-Attack Detection | Go-Decomposition Algorithm | ✓ | - | ✓ |
[20] | Intrusion Detection and Vulnerability Analysis | Markov Decision Process-Based Method | - | ✓ | ✓ |
[21] | Intrusion Detection and Vulnerability Analysis | Huber M-Estimator | - | ✓ | ✓ |
[39] | Cyber-Attack Vulnerability Analysis | State Estimation | ✓ | - | ✓ |
[40] | Cyber-Attack Vulnerability Analysis | State Estimation Based on Power Flow Analysis | ✓ | ✓ | - |
[41] | Cyber-Attack Vulnerability Analysis | State Estimation | ✓ | - | - |
[42] | Cyber-Attack Detection and Identification | Zero-Sum Static Game Theory | ✓ | - | - |
[43] | Cyber-Attack Detection | Game Theory Based on Minimax-Regret Method | ✓ | ✓ | ✓ |
[44] | Cyber-Attack Detection and Identification | Game Theory | ✓ | - | ✓ |
[45] | Cyber-Attack Detection | Game Theory | ✓ | ✓ | - |
[46] | Cyber-Attack Detection and Vulnerability Analysis | Dynamic Game Theory | ✓ | - | - |
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Mohammadi, F. Emerging Challenges in Smart Grid Cybersecurity Enhancement: A Review. Energies 2021, 14, 1380. https://doi.org/10.3390/en14051380
Mohammadi F. Emerging Challenges in Smart Grid Cybersecurity Enhancement: A Review. Energies. 2021; 14(5):1380. https://doi.org/10.3390/en14051380
Chicago/Turabian StyleMohammadi, Fazel. 2021. "Emerging Challenges in Smart Grid Cybersecurity Enhancement: A Review" Energies 14, no. 5: 1380. https://doi.org/10.3390/en14051380
APA StyleMohammadi, F. (2021). Emerging Challenges in Smart Grid Cybersecurity Enhancement: A Review. Energies, 14(5), 1380. https://doi.org/10.3390/en14051380