Metadata-Version: 2.1
Name: titli
Version: 0.0.3
Summary: A library for collection of IDS and tools for evaluating them
Home-page: https://github.com/spg-iitd/raids
Author: Subrat Kumar Swain
Author-email: mailofswainsubrat@gmail.com
License: MIT
Keywords: ids adversarial network nids
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Security
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: scapy
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: matplotlib
Requires-Dist: scikit-learn
Requires-Dist: scipy
Requires-Dist: tqdm
Requires-Dist: torch
Requires-Dist: torchvision

# Titli
Artificial Intelligence based Intrusion Detection Systems

![PyPI - Python Version](https://img.shields.io/pypi/pyversions/titli)
![PyPI - Version](https://img.shields.io/pypi/v/titli)
![GitHub License](https://img.shields.io/github/license/spg-iitd/titli)

### Installation
```
pip install titli
```

### Usage
- Step 1: Copy the ```examples/train_ids.py``` and ```examples/test_ids.py``` file from the repo to your local machine.
- Step 2: Run both the files to train and test the Kitsune IDS respectively.

### Todo (Developer Tasks)
- [ ] Check if RMSE is used for loss or just the difference.
- [ ] Put Kitsune code into the base IDS format.
- [ ] Write code to evaluate the model and calculate all the metrics.  
