# A Survey of Game Theoretic Approaches to Modelling Decision-Making in Information Warfare Scenarios
## 4 Games for Representing Information Warfare Operations
### A Taxonomy of Information Warfare Games
#### 4.2.6 Information Attack and Hacker Warfare Games
The interaction between the computer system (defender) and the attacker(s) in this study is modeled as a multi-stage games. The aim of the computer system is to optimize its security from cyber-attacks. On the other hand, the attacker aims to maximize his/her attacks on the security. A novel approach is proposed to predict different types of attacks. More specifically, the study provides a model to predict attacks on IDS-protected systems and a model for credit card fraud detection. [PERSON] et al. [78] propose a novel risk assessment model for the network information system based on Markov game theory. Two players are considered in this study: treat agent (attacker) who launch the attacks and the vulnerability agent who mitigates the risks by repairing the vulnerability of the system. The Markov game method is used in this study to estimate the belief of each cyber-attack pattern and suggest the best response to counter those attacks. Simulation results show the effectiveness of the proposed method. A number of studies reviewed by [PERSON] et al. [79] fall under the category of personal hacker warfare [80; 81]. Based on evolutionary game theory, [80] propose an active defense model to protect wireless sensor nodes from attackers. This study considers the specific scenario where the attackers try to plunder resource from other nodes to extend their lifetime. The proposed defense model allows the wireless sensor nodes to dynamically adjust their defensive strategies based on different strategies of the attackers. Simulation results show that the proposed model improves the performance of the wireless sensor networks and greatly saves energy consumption. [PERSON] et al. [81] consider the security issues that arise for centralized coordinator nodes in wireless sensor networks. In this study, the attackers are considered to be a kind of malicious nodes which aim to disrupt the performance of the coordinator nodes by strategic jamming attack. To address this problem, a coordinator selection scheme and a stochastic game model for dynamic defense are presented. Simulation results indicate that by selecting a new coordinator node that are not attacked by malicious entity, the lifetime and reliability of the wireless sensor networks can be improved. [PERSON] et al. [82] handle the problem of how a system of multiple nodes can be protected against stealthy attacks. The interaction between the attacker and the defender is modelled as a two player-non-zero-sum game where both players have limited resources. Specifically, an asymmetric feedback model is considered where the moves of the defender are fully observable while the moves of the attacker are stealthy. This study analyses the optimal strategies for both players and characterizes the Nash Equilibrium of the game. Table 8 shows a summary of personal hacker warfare games mentioned above. Corporate Hacker Warfare Games  
A vast increase in the use of the internet for business purposes has exposed corporate to face greater risks for cyber-attacks. To better understand the interaction between corporate and attackers, [PERSON] and [PERSON] [83] propose a game theoretic approach which specifically considers economic motivations for investment in internet security. In particular, this study investigate a scenario in which firms/corporates plan for long-term security investment by considering the likelihood of cyber-attacks. A game theoretic approach to modelling decision-making in information security investment has also been considered [84]. In this study, security investments were modelled in several types of games which cover common practical security situations. In each game, players are able to choose two independent decision parameters. The first parameter is the protection level which relates to