| Title | Anomaly Detection in Smart Grids: A Survey From Cybersecurity Perspective |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Alkuwari, Ahmad N., Al-Kuwari, Saif, Qaraqe, Marwa |
| Conference Name | 2022 3rd International Conference on Smart Grid and Renewable Energy (SGRE) |
| Keywords | anomaly detection, attack surface, compositionality, Data models, energy theft, feature extraction, human factors, power consumption, Predictive models, pubcrawl, renewable energy sources, resilience, Resiliency, Smart grid, Smart Grid Sensors, Smart grids, smart meters, Soft sensors |
| Abstract | Smart grid is the next generation for power generation, consumption and distribution. However, with the introduction of smart communication in such sensitive components, major risks from cybersecurity perspective quickly emerged. This survey reviews and reports on the state-of-the-art techniques for detecting cyber attacks in smart grids, mainly through machine learning techniques. |
| DOI | 10.1109/SGRE53517.2022.9774221 |
| Citation Key | alkuwari_anomaly_2022 |
Anomaly Detection in Smart Grids: A Survey From Cybersecurity Perspective