Network-Intrusion-Detection-using-UNSW-NB15

Network Intrusion Detection using UNSW-NB15: Comparative Analysis of Machine Learning Models Delve into network intrusion detection utilizing the UNSW-NB15 dataset, a benchmark in cybersecurity. This project involves an in-depth exploration of various machine learning models, including Deep Neural Networks (DNN), XGBoost, CNN, Navie Bayes, Logistic Regression (LR), and Ensemble methods. Through a comparative analysis, discover the effectiveness of these models in categorizing network traffic into diverse attack categories present in the UNSW-NB15 dataset. Gain insights into the performance variations among different algorithms and their implications for bolstering cybersecurity measures.