Machine Learning Methods for Network Security Optimization: Exploring the Power of Decision Tree Algorithms
Pratibha Verma, Latika Tamrakar, Sanat Kumar Sahu · 2025
Firewalls play a vital role in securing network infrastructure by filtering and monitoring incoming and outgoing network traffic. Firewall log files encompass valuable information about network activities, including potential security threats. However, analyzing these log files manually is a time-consuming and error-prone task. With the continuous improvement in Information and Communication Technology (ICT), firewall dataset is stored in the electronic form and accessed remotely according to the requirements. However, there is a negative impact like unauthorized access, misuse, stealing of the data, which violates the privacy concern of computer network. It is critical and in demand in today's era to analyse firewall devices and control internet traffic based on the findings of these investigations. In this research paper, we propose an intelligent method for monitoring firewall log files using classification methods, specifically Random Forest (RF), C4.5, and Classification and Regression Tree (CART), along with the feature selection technique (FST) of Information Gain (IG). The objective is to automate the process of detecting and classifying network activities in real-time, aiding security administrators in identifying and mitigating potential threats efficiently. In final step compared the outcome of the performance of classifiers with all and selected features.