# Risk Assessment of UAV Cyber Range Based on Bayesian-Nash Equilibrium
## 2 Related Research Work
### Risk Assessment of UAV  
UAVs typically rely on radio communications to transmit data and control commands. SDR technology [17] can be used to simulate and analyze signals in UAV cyber communication to identify potential vulnerabilities and threats. On the one hand, with SDR equipment, it is possible to simulate malicious attacks, test the defense mechanisms of the UAV cyber range, and assess its ability to withstand attacks. On the other hand, SDR equipment can be used to create complex communication scenarios to test the performance of the UAV cyber range in multiple situations. UAV cyber communication is not limited to Wi-Fi protocol, as it may also involve other communication protocols such as LoRa, UAV-to-UAV direct communication, etc. SDR technology has irreplaceable applications in the identification and analysis of Wi-Fi, LTE, UAV-to-UAV communication risk. [PERSON] et al. [18] analyzed the current situation of information security risk assessment at home and abroad, assessment system models, assessment standards, assess ment methods, and assessment process, discussed the assessment systems at home and abroad, pointed out the problems to be solved in the current information security risk assessment, and looked forward to the development prospect of information security risk assessment. [PERSON] et al. [19] introduced the research status and progress of stochastic models and evaluation techniques of cyber security, and summarized several research methods and evaluation techniques of stochastic models of cyber security. As regards the attack tree, [PERSON] [20] proposed the method of using an attack tree to describe system security in a formal and systematic way to model a single-vulnerability threat. [PERSON] [21] elaborated that the attack tree, which expresses the attack change in a recursive or progressive way, can more directly reflect the steps of the attacker to implement the attack. As regards the privilege graph, [PERSON] et al. [22] put forward the concept of the privilege graph to express the changes in the attackers' control permissions on the system caused by system vulnerabilities and to evaluate the security of the system. A metric is defined for vulnerability to express the probability of success of an attack on the vulnerability. [PERSON] et al. [23] proposed a cyber risk evaluation experimental model framework based on the idea of the privilege graph. In terms of attack graphs, [PERSON] and [PERSON] proposed the graph-based cyber vulnerability analysis method [24]. This method can test all possible results after a successful attack, and it indicates the attack paths with high probability of success that an attacker can take to obtain different risks faced by cyber information assets. As regards model checking, [PERSON] et al. [25] firstly put forward the application of the model-checking method to the comprehensive analysis of host weaknesses, and implemented a vulnerability analysis tool under UNIX system. [PERSON] and [PERSON] [26] extended the application of model checking to the evaluation of cyber systems. [PERSON] et al. [27] proposed a risk communication model composed of risk cyber and risk communication algorithm. The risk cyber describes the access relationship structure and risk situation of the cyber system, and the risk communication algorithm gives the movement rules of risks. We not only focus on the vulnerability of Wi-Fi communications, but also look at other wireless communication protocols and control mechanisms such as Bluetooth [28], ZigBee [29], 5G [30], and satellite communications [31]. We provide an in-depth analysis of the security of these wireless technologies, including their encryption strength, authentication mechanisms, and anti-jamming capabilities.