Machine Learning-Based Cyberattack Prediction Models and Their Effectiveness in Cybersecurity

Abstract

This research paper aims to analyze cyberattack prediction models based on machine learning. This was done by evaluating the fundamental machine learning algorithms as the most critical component of these models. The results of the current research paper demonstrate the effectiveness of machine learning in expanding the capabilities of threat detection and offer a basis for implementing these models in real-time cybersecurity systems. In addition, the main problems of artificial intelligence technologies were mentioned, which include financial constraints and the need for a large amount of data for their training.