Network Security Situation Awareness Approach Based on Markov Game Model
基于Markov 博弈模型的网络安全态势感知方法

To analyze the influence of propagation on a network system and accurately evaluate system security, this paper proposes an approach to improve the awareness of network security, based on the Markov Game Model (MGM). This approach gains a standard data of assets, threats, and vulnerabilities via fusing a variety of system security data collected by multi-sensors. For every threat, it analyzes the rule of propagation and builds a threat propagation network (TPN). By using the Game Theory to analyze the behaviors of threats, administrators, and ordinary users, it establishes a three player MGM. In order to make the evaluation process a real-time operation, it optimizes the related algorithm. The MGM can dynamically evaluate system security situation and provide the best reinforcement schema for the administrator. The evaluation of a specific network indicates that the approach is suitable for a real network environment, and the evaluation result is precise and efficient. The reinforcement schema can effectively curb the propagation of threats.