## 1 Introduction  
Wind energy has been recognized as one of the major renewable energy sources for over two decades. As of 2019, the global wind power capacity reaches 60 GW, including onshore and offshore plants [1]. Nowadays, it is typical to install multiple turbines in the same area where wind energy is abundant, this is called a wind farm. To manage a wind farm consisting of several to hundreds of turbines efficiently, a network-based monitoring and control scheme is needed, such as supervisory control and data acquisition (SCADA) systems. By virtue of SCADA systems, it is possible to acquire the condition of the wind turbines installed over a wide area and manage them efficiently. However, network-based control and monitoring systems, including SCADA systems, are frequently targeted by cyberattacks due to the presence of the network. Recently, several attempts of cyberattacks on network-controlled plants have been reported, including a German steel mill [2], Iranian and American nuclear facilities [3], Ukrainian power plant [4], among others. These cases imply that many systems using network-based control and monitoring systems, including the wind turbine systems, are not free from cyberattacks. In order to secure the networked control systems from possible cyberattacks, researches on cyberattacks and defense strategies have drawn attention, see, e.g., [5, 6, 7, 8], surveys [9, 10, 11] and the references therein. Cyberattacks on systems controlled through networks can be classified into two categories, model-free attacks and model-based attacks. The model-free attacks are basically accomplished in the form of overloading the system through superfluous requests or stealing information from network lines. A most well-known model-free attack is DoS (denial-of-service) [12]. An attacker running DoS may overload or possess the network and system resources by sending numerous requests to the target system, disturbing the normal operation of systems. DDoS (distributed denial-of-service) [13], which conducts DoS attacks in a distributed form, and PSDoS (power save denial-of-service) [14] methodsthat can conduct DoS attacks with relatively small attack resources, are variants of DoS. Eavesdropping [15] is another instance of model-free attacks, which is accomplished by occupying part of the network lines. The eavesdroppers collect information by intercepting data or signals that are sent over the network. A Replay attack [16] is performed by combining the above two attacks. An attacker running the replay attack steals data being transmitted and sends it to the system repeatedly, pretending that the requests are from the valid user. The model-based attacks are another category of cyberattack that include covert false-data injection attacks [17], zero-dynamics attacks (ZDAs) [8], robust zero-dynamics attacks [18], and pole-dynamics attacks [19]. An attacker performing the covert false-data injection attack, targeting a system that has known dynamics, can make the remote monitoring system or controller recognize that the system is under normal operation, even though it is not. ZDA is another model-based attack that manipulates the input signal only with the knowledge of the system dynamics. The attacker of ZDA can make the internal states of the system become unbounded while making the impact of the attack hardly visible on the output. The pole-dynamics attack is an attack that a malicious signal is injected into the output of the system. One of the major features of the model-based attack is that it allows more sophisticated and clever attacks. The attack signals, generated by using knowledge of the target systems, lead the remote monitoring system to be mistaken as a normal operation, which implies that the attacks are stealthy. In this paper, we are particularly interested in the zero-dynamics attack on wind turbine systems. ZDA is known as one of the most fatal cyberattacks and this is mainly because the attack exploits the system model and very hard to detect.