Network Anomaly Detection
This repository contains code and resources for detecting network anomalies using machine learning techniques.
Table of Contents
Introduction
Network anomaly detection is crucial for identifying unusual patterns that may indicate security threats or performance issues. This project aims to provide a robust solution for detecting such anomalies in network traffic.
Installation
To get started, clone the repository and install the required dependencies:
git clone git@github.com:phierhager/network-anomaly.git
cd network-anomaly
poetry install
poetry shellDatasets
To be able to train, download the UNSW-NB15 dataset from here (https://www.kaggle.com/datasets/dhoogla/unswnb15) or the CIC-IDS2017 dataset from here (https://www.kaggle.com/datasets/dhoogla/cicids2017) and save them in a data/ folder on top level.
Usage
To train a detection model refer to the train_tutorial.ipynb notebook. The real-time package inspection is under development.