Intrusion Detection System Using PCA With Machine Learning Classifiers

The main objective of the Intrusion Detection System (IDS) using Principal Component Analysis (PCA) with machine learning classifiers is to develop a robust system that can effectively detect and classify intrusions or malicious activities in computer networks, leveraging the dimensionality reduction capabilities of PCA and the predictive power of machine learning algorithms. This system aims to enhance network security, identify potential threats, and enable prompt responses to ensure the integrity and confidentiality of the network.