## 1 Introduction  
Thanks to the global initiative to reduce the effects of energy production on climate change, distributed energy resources (DER) have become an important contributor to the modern power grid, with wind energy being the preferred DER implemented globally. According to the Pacific Northwest National Laboratory, wind energy represents more than 10 percent of the electricity produced in the United States, making it the largest contribution of renewable power generation in the nation [1]. On 21 November 2023, the [PERSON] administration announced its approval of the Empire Wind Project, the sixth approval of an off-shore wind energy project under the administration, supporting President [PERSON]'s goal of 30 GW of offshore wind energy capacity by the year 2030 [2]. Many wind farms are in very remote locations or offshore and are subject to right-of-way constrictions of local and regional municipalities, and due to their incredible size, finding the right location can be challenging. To optimize the energy produced by wind farms, a detailed analysis of wind power flow through possible site locations must be performed to insure the investment in wind energy yields not only a steady supply of energy, but also reliable profits for investors [3]. To help alleviate these constraints, remote internet-of-things (IoT) devices are becoming a common solution to monitor, control, and manage wind farm power systems. There are several different types of wind turbine generators, and depending on the available resources such as location, budget, and municipal regulations, the optimal generator should be implemented. In the last few decades, synchronous generators, such as the permanent magnet synchronous generator, have been used due to their high reliability. However, due to wind speeds being variable, an expensive gear box, torque converter, and speed converter are necessary to maintain the synchronous speed of the generator [4]. Due to these issues, many modern wind farms are implementing induction generators, such as the double-fed induction generator (DFIG), due to their lower costs and variable speeds [5]. Induction generators are variable-speed, so they do not require a sophisticated gearbox to maintain a synchronous speed. However, they do require intelligent electronic devices such as AC/DC converters, voltage source converters inverters (VSC), and a step-up gearbox, and they may also use energy storage systems to remove any fluctuations in the generator frequency and to boost power output when wind speeds are low, as reported in ref. [6]. Because DFIGs allow for the decoupling of real and reactive power through the independent control of torque and rotor excitation currents, they have become a preferable generator for modern wind farms. Figure 1 depicts a grid connected DFIG-based wind turbine generator model with pitch angle control and a rotor-side converter, grid-side converter, DC-link capacitor, turbine blades, rotor shaft, and set-up gearbox. With the increased implementation of IoT devices in wind farm control schemes, major cybersecurity risks have arisen that, if not rectified quickly, could lead to major losses in revenue for power providers, as well as unstable and unreliable power for consumers. Historically, cyber attacks on wind farms have been isolated to ransomware attacks, which involve hacking into a vendor's wide area network (WAN) and stealing as much data as possible before severing communication lines to control devices and holding the data and devices hostage until a monetary demand is met. On 19 November 2021, a wind farm operated by the Danish wind turbine manufacturer Vestas was attacked by a LockBit ransomware attack that stole sensitive proprietary data and employee personal information [7]. Thanks to the quick response of Vestas's cyber response team, no third-party vendors were affected, and no damage was reported in any wind farms [7]. In March 2022, the wind farm operator Enceron lost control of their satellite communication with approximately 5800 wind turbine generators [7].