Preemptive Prediction-Based Automated Cyberattack Framework Modeling

Abstract

As the development of technology accelerates, the Fourth Industrial Revolution, which combines various technologies and provides them as one service, has been in the spotlight, and services using big data, Artificial Intelligence (AI) and Internet of Things (IoT) are becoming more intelligent and helpful to users. As these services are used in various fields, attacks by attackers also occur in various areas and ways. However, cyberattacks by attackers may vary depending on the attacking pattern of the attacker, and the same vulnerability can be attacked from different perspectives. Therefore, in this study, by constructing a cyberattack framework based on preemptive prediction, we can collect vulnerability information based on big data existing on the network and increase the accuracy by applying machine learning to the mapping of keywords frequently mentioned in attack strategies. We propose an attack strategy prediction framework.