Anomaly detection has been the main focus of many researchers’ due to its potential in detecting attacks.
The main objective of this project is to develop a systematic approach to generate diverse and comprehensive benchmark dataset for intrusion detection based on the creation of user profiles which contain abstract representations of events and behaviours seen on the network.
In this work, I've developed an Intrusion-Detection_system(IDS) model using a network traffic dataset containing the most common network attacks.