2n3g5c9/smart-network-sensor

🔦 Meta-alerting compression of NIDS sensors data based on anomaly detection (old project).

Foreword   •   Getting started   •   Tech/frameworks used   •   License

✍️ Foreword

NIDS sensors can generate a tremendous number of alerts (most often false positives) that are hard to make sense of. Here are analyzed 3 public datasets, and resulted in a 96-98% compression ratio over the number of generated alerts.

🏁 Getting started

Prerequisites

You must have Python 3.7 and Jupyter installed, as well as the Python dependencies specific to the project (you can use Pipenv).

Installation

Clone the repository:

git clone https://github.com/2n3g5c9/smart-network-sensor && cd smart-network-sensor

How to use

Simply install the dependencies and run jupyter:

jupyter notebook

🪄 Tech/frameworks used

• Jupyter: Open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text.
• Python 3: Programming language that lets you work quickly and integrate systems more effectively.

📃 License

This project is licensed under the MIT License - see the LICENSE file for details