Enhancing Cyber Threat Intelligence Through Supervised Machine Learning: A Comprehensive Classification Approach

The primary goal of cyber threat intelligence (CTI) is to give advanced and deep knowledge about threat landscape in order to maintain internal and external safeguards against advanced cyberattacks. The fundamental issue is inaccurate, incomplete, outdated, and invaluable threat intelligence. As a result, one of the emerging solutions to the threat information sharing is data analysis based on AI algorithms. In this paper, we introduced a supervised learning-based system that provides a sophisticated classification of cyber threats and risks to improve threat information sharing. Extensive simulations are performed to validate the proposed approach and compare it to numerous supervised learning techniques in terms of accuracy, precision, recall, f1-score, and total support.