How machine learning is tackling cyber-attack detection in wind turbines: New findings were presented at AIE 2024

As wind energy continues to power a growing share of the global energy mix, wind turbines have become prime targets for sophisticated cyber-attacks that threaten to disrupt operations and cause cascading failures. In response, researchers are leveraging machine learning to develop advanced detection strategies tailored specifically to these stealthy cyber-attacks. At AIE 2024, our new research findings were presented, showcasing how machine learning-based normal behavior models can effectively identify anomalies caused by coordinated cyber-attacks on wind turbines, offering a promising solution to this emerging challenge.

H. Wu, H. Badihi, Y. Xue, and M. Vilkko, “A normal behavior model based on machine learning for wind turbine cyber-attack detection,” in Proc. of the International Workshop on Artificial Intelligence and Machine Learning for Energy Transformation (AIE), Vaasa , Finland, May 20-22, 2024.