Watermark-Based Replay Attack Detection for Unmanned Marine Vehicles

This paper is concerned with the problem of attack detection for unmanned marine vehicles (UMV) suffering from replay attacks. With the openness of the communication network, replay attacks occur at a higher rate and can cause severe impacts on UMV. Therefore, it is of great significance to detect replay attacks promptly and efficiently. To this end, an attack detection scheme based on watermark signals is proposed. Firstly, a Takagi-Sugeno (T-S) fuzzy system model for the UMV are established. Then, encoded and decoded signals based on the watermark signal are constructed, which are added to terminals of the sensors and the state estimators to detect replay attacks. The signals can effectively affect the residual values of the system when it is under attack, thus enabling the detection of replay attacks. Moreover, the method contributes to less system performance loss is demonstrated. Finally, the simulation results verify the effectiveness of this scheme.