Machine LearningExplainable AINot deployed
Machine Learning-Based Intrusion Detection System with Explainable Artificial Intelligence
A machine learning-powered security system that detects malicious activities in computer networks using multiple classification models and explainable AI to identify threats and interpret the factors behind detection decisions.
The project evaluates Decision Tree, Random Forest, Support Vector Machine, and XGBoost models, alongside a soft-voting ensemble, to investigate intrusion detection performance.
PythonScikit-learnXGBoostCybersecurity