Visible to the public A Method of Cyber Risk Control Node Selection Based on Game Theory

TitleA Method of Cyber Risk Control Node Selection Based on Game Theory
Publication TypeConference Paper
Year of Publication2018
AuthorsQiu, Yanbin, Liu, Yanhua, Li, Shijin
Conference NameProceedings of the 8th International Conference on Communication and Network Security
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-6567-3
Keywordscomposability, control theory, cyber attack, game theory, offensive and defensive income, pubcrawl, resilience, Resiliency, risk control, security, Vulnerability
Abstract

For the occurrence of network attacks, the most important thing for network security managers is how to conduct attack security defenses under low-risk control. And in the attack risk control, the first and most important step is to choose the defense node of risk control. In this paper, aiming to solve the problem of network attack security risk control under complex networks, we propose a game attack risk control node selection method based on game theory. The method utilizes the relationship between the vulnerabilities and analyzes the vulnerability intent information of the complex network to construct an attack risk diffusion network. In order to truly reflect the different meanings of each node in the attack risk diffusion network for attack and defense, this paper uses the host vulnerability attack and defense income evaluation calculation to give each node in the network its offensive and defensive income. According to the above-mentioned attack risk spread network of offensive and defensive gains, this paper combines game theory and maximum benefit ideas to select the best Top defense node information. In this paper, The method proposed in this paper can be used to select network security risk control nodes on complex networks, which can help network security managers to play a good auxiliary role in cyber attack defense.

URLhttps://dl.acm.org/citation.cfm?doid=3290480.3290504
DOI10.1145/3290480.3290504
Citation Keyqiu_method_2018