| Title | An Approach on Attack Path Prediction Modeling Based on Game Theory |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Yang, SU |
| Conference Name | 2021 IEEE 5th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) |
| Keywords | advanced persistent threat, Analytical models, APT attack, game model, game theory, Games, Human Behavior, information technology, Metrics, network defense framework, Organizations, Predictive models, pubcrawl, Resiliency, Scalability, security |
| Abstract | Considering the lack of theoretical analysis for distributed network under APT (advanced persistent threat) attacks, a game model was proposed to solve the problem based on APT attack path. Firstly, this paper analyzed the attack paths of attackers and proposed the defensive framework of network security by analyzing the characteristics of the APT attack and the distributed network structure. Secondly, OAPG(an attack path prediction model oriented to APT) was established from the value both the attacker and the defender based on game theory, besides, this paper calculated the game equilibrium and generated the maximum revenue path of the attacker, and then put forward the best defensive strategy for defender. Finally, this paper validated the model by an instance of APT attack, the calculated results showed that the model can analyze the attacker and defender from the attack path, and can provide a reasonable defense scheme for organizations that use distributed networks. |
| DOI | 10.1109/IAEAC50856.2021.9391078 |
| Citation Key | yang_approach_2021 |
An Approach on Attack Path Prediction Modeling Based on Game Theory