Metadata-Version: 2.1
Name: network_intrusion_detection
Version: 0.1.4
Summary: A Python package for CNN-LSTM model pre-trained on CICIDS2017 and finetuned on UNSW-NB15 for network intrusion detection.
Author: ID: 2319323
Author-email: 2319323@chester.ac.uk
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: tensorflow
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: scikit-learn
Requires-Dist: imbalanced-learn

# Intrusion Detection Package

This package provides a CNN-LSTM-based intrusion detection model that can be used to classify network traffic as benign or malicious.

## Installation

You can install the package using pip:

pip install net_intrusion_detection


## Usage

To use the model, follow these steps:

1. Load your pre-trained model (.h5 file).
2. Preprocess your network traffic data (CSV format).
3. Make predictions on the data.

Example:

```python
from network_intrusion_detection import make_prediction

predictions = make_prediction('path_to_model.h5', 'path_to_csv_file.csv')
print(predictions)
