Network Attack Intention Recognition Based on Signaling Game Model and Netlogo Simulation
Xiaoning Zhang, Hengwei Zhang, Chenwei Li, Pengyu Sun, Zhilin Liu, Jindong Wang · 2021
With the development of attack technology, identifying the real intention of network attack and avoiding further deterioration of security situation has become a hot research topic in recent years. This paper proposes an attack intention recognition method based on signaling game model. Firstly, we generate attack intention hypotheses, and then calculate the probability of each attack intention by solving game equilibrium. Experiments show that the method can effectively improve the accuracy of attack intention recognition from the perspective of the revenue.