Keywords
Adaptive watermarking
Kalman filtering
Residual detection
Submitted : 2026-03-23
Accepted : 2026-04-07
Published : 2026-04-22
Abstract
With the increase in the scale and complexity of offshore wind power systems, zero-dynamics attacks pose a severe threat to the cyber security of such systems. Their concealment makes them difficult to detect using traditional output observation-based methods. To address this problem, this paper proposes a zero-dynamics attack detection framework integrating adaptive watermarking and Kalman filtering, which achieves effective attack identification by embedding an adaptive watermark into the system input and conducting residual analysis. Simulation results show that the proposed method can quickly detect zero-dynamics attacks without affecting the normal operation of the system.
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