Establishment of response evaluation model and empirical study of risk in enterprise threat intelligence
Jianian Zhu, Kai Zou, Xuchong Liu, Kai Gao · 2020 2nd International Conference on Economic Management and Model Engineering (ICEMME) · 2020
In order to make up for the deficiency of enterprise threat intelligence response mechanism, a scientific enterprise threat intelligence response evaluation model is proposed and the enterprise risk is empirically evaluated and analyzed. The enterprise threat intelligence response model was constructed based on the four main influencing factors of enterprise personnel quality, software/hardware facilities, technical support, and management awareness. The RBF neural network improved by grey Wolf swarm optimization algorithm was used for training and simulation, so as to conduct in-depth analysis and research. The results show that: 1. RBF neural network can make up for the deficiency of RBF neural network by optimizing grey Wolf pack; 2. While focusing on technological innovation and personnel training in the threat intelligence response system, enterprises cannot ignore the importance of management awareness.