https://github.com/2n3g5c9/smart-network-sensor
🔦 Meta-alerting compression of NIDS sensors data based on anomaly detection (old project).
https://github.com/2n3g5c9/smart-network-sensor
jupyter keras nids-sensors tensorflow
Last synced: 3 months ago
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🔦 Meta-alerting compression of NIDS sensors data based on anomaly detection (old project).
- Host: GitHub
- URL: https://github.com/2n3g5c9/smart-network-sensor
- Owner: 2n3g5c9
- License: mit
- Created: 2019-04-21T18:00:12.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2022-12-26T21:45:11.000Z (over 3 years ago)
- Last Synced: 2024-05-28T16:20:18.629Z (about 2 years ago)
- Topics: jupyter, keras, nids-sensors, tensorflow
- Language: Jupyter Notebook
- Homepage:
- Size: 10.6 MB
- Stars: 0
- Watchers: 3
- Forks: 0
- Open Issues: 9
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
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](https://www.python.org/downloads/)** and **[Jupyter](https://jupyter.org/install)** installed, as well as the Python dependencies specific to the project (you can use **[Pipenv](https://github.com/pypa/pipenv)**).
### Installation
Clone the repository:
````bash
git clone https://github.com/2n3g5c9/smart-network-sensor && cd smart-network-sensor
````
### How to use
Simply install the dependencies and run `jupyter`:
````bash
jupyter notebook
````
## 🪄 Tech/frameworks used
- [Jupyter](https://jupyter.org/): Open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text.
- [Python 3](https://www.python.org/): Programming language that lets you work quickly and integrate systems more effectively.
## 📃 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details