# Enhancing Unmanned Marine Vehicle Security: A Periodic Watermark-Based Detection of Replay Attacks
###### Abstract  
This paper explores a periodic watermark-based replay attack detection method for Unmanned Marine Vehicles modeled in the framework of the Takagi-Sugeno fuzzy system. The precise detection of replay attacks is crucial for ensuring the security of Unmanned Marine Vehicles; however, traditional timestamp-based or encoded measurement-dependent detection approaches often sacrifice system performance to achieve higher detection rates. To reduce the potential performance degradation, a periodic watermark-based detection scheme is developed, in which a compensation signal together with a periodic Gaussian watermark signal is integrated into the actuator. By compensation calculations conducted with all compensatory signals in each period, the position corresponding to a minimum value of the detection function can be derived. Then, the time that the attacks occurred can be ensured with the aid of the comparison between this position with the watermark signal in the same period. An application on a UMV is shown to demonstrate the effectiveness of the presented scheme in detecting replay attacks while minimizing control costs. unmanned marine vehicles; replay attack detection; periodic watermark signal; Takagi-Sugeno fuzzy system +
Footnote †: journal: Applied  
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require prior knowledge of the control systems. These attackers typically retransmit system measurement data from periods of stability, rendering the attacks inherently covert and difficult to detect through standard methods [18]. The covert nature of replay attacks makes them challenging to detect with traditional methods, which contributes to their frequent occurrence in contemporary UMV systems. The rising occurrence of replay attacks has drawn the interest of scholars, especially in the aspect of attack detection. Existing methods primarily include timestamp techniques and the addition of physical watermarks to control signals. Timestamp-based replay attack detection was first proposed in [19], where Kerberos leverages a reputable third-party authentication service to authenticate user identities. Subsequently, [PERSON] et al. [20] proposed an enhanced remote keyless entry system employing timestamping and exclusive OR (EOR) encoding to robustly defend against replay attacks, significantly improving security over systems. [PERSON] et al. [21] introduced a timestamp-based method to enhance ZigBee network security against replay attacks, ensuring effectiveness without impacting network efficiency. Furthermore, a Promela-based model checking approach for verifying timestamp-utilizing security protocols against replay attacks, effectively identifying vulnerabilities in the protocol, was proposed in [22]. Nonetheless, it had been suggested by [PERSON] et al. [23] and [PERSON] et al. [24] that transmitted signals are vulnerable to interception by replay attackers, who can alter the timestamps, leading to noticeable decline in the efficiency of the detection strategy mentioned in [19; 20; 21; 22]. To address this issue, [PERSON] et al. [25] added the continuous addition of Gaussian random noise to the control signals, causing noticeable variations in data residuals before and after an attack, therefore facilitating the detection of such attacks. Then, an approach for designing optimal physical watermark signals to detect replay attacks in linear time-invariant systems with unknown parameters was studied in [26]. These strategies adjusted the system's optimal control signals, trading off control costs for improved detection of attacks. Therefore, an optimized watermarking method that balances improved detection of replay attacks against control costs in networked control systems was discussed in [27]. [PERSON] et al. [28] presented a watermarking method for efficiently detecting transient covert attacks in industrial cyber-physical systems, reducing system performance cost while detecting detection accuracy.