The data used for this is a subset of an open source default of Intrusion detection evaluation dataset (ISCXIDS2012) from the the Canadian Institute for Cybersecurity repository: https://www.unb.ca/cic/datasets/ids.html.
The purpose of this project is Network anomaly detection which is the main machine learning task solved by different algorithms correlating to the identification of rare items, events or observations which raise suspicions by differing significantly from the majority of the data. In essence, anomaly detection can be used as a tool for many other tasks, such as intrusion detection, fraud detection, fault detection, system health monitoring, event detection in sensor networks, detecting ecosystem disturbances, and defect detection in images using machine vision, etc.