# Risk Assessment of UAV Cyber Range Based on Bayesian-Nash Equilibrium
## 3 Application of Attack-Defense Tree Model in UAV Cyber Range  
### Attack-Defense Tree Model with Economic Indicators  
In recent years, in the field of computer cyber security, some scholars have begun to apply game theory to analyze the problem of offensive and defensive confrontation and offensive and defensive strategy of cyber security. However, the UAV system is different from the traditional information system; so, it cannot blindly learn from the strategy selection method applied in the field of computer cyber security. In the course of establishing the game model of attack and defense of the UAV cyber range, the determination of the income function is very important.  
In traditional computer cyber security game analysis, the three attributes of information confidentiality, integrity and availability are used as basic evaluation indexes to construct the income function matrix for analysis. The method proposed in this paper is different from the revenue function construction method in the traditional computer cyber system, but based on the traditional attack and defense tree model, considering the economic cost and benefit of attack and defense, _DPF_ and _APF_ represent the defense benefits and attack benefits of both sides of the UAV range, and construct the revenue matrix. Then, the relevant game theory knowledge is used to build a game model for predictive analysis.  
The attack tree describes the many ways in which a UAV range can be attacked. It uses a tree structure to represent various attack behaviors against UAV. Based on the basic attack tree model, each attack node is attached to one or more defense measures to obtain an attack-defense tree.  
The defense side of the UAV range decides to adopt two strategies of defense and non-defense against the target UAV cyber, and the attacker decides whether to attack the target UAV cyber range or not. In order to simulate and deal with the problem of offensive and defensive game strategy of the UAV cyber range, virtual player \"0\" is introduced according to [PERSON]'s idea, that is, \"nature\". \"Nature\" first selects the type of defense, where the defense mainly refers to the defense cost.  
In the game of attack and defense of UAV cyber range, regardless of whether it is attack or defense, it is costly. By introducing a virtual player, \"nature\", this player does not have to consider his own gains and losses; its only role is to give the type vector \(\theta=(\theta_{1},\theta_{2},\cdots,\theta_{n})\) of each player in the attack and defense game of the UAV cyber range, where \(\theta_{i}\in\Theta_{i}\) the feasible type space and \(\Theta_{i}\) is a complete description of the characteristics of the player \(i\).  
In the actual combat of cyber-attack and -defense of the UAV range, there are generally two types of attackers: adventurous attackers and conservative attackers. The attacker does not want the defender to know which type he belongs to. Obviously, with different types, the attack strategy chosen by the attacker and the effect of the attack are different. Since the attacker makes the decision in advance, the result of its choice will be understood by the defender and the decision will be made.  
In order to facilitate the analysis of offensive and defensive game by using the attack and defense tree model of UAV cyber range, two important economic indicators, namely _DPF_ and _APF_, are introduced, which are important bases for the subsequent analysis and calculation of the return matrix of offensive and defensive game. The meanings and calculation methods of both are discussed below.