|
--- |
|
language: |
|
- en |
|
pipeline_tag: text-classification |
|
license: agpl-3.0 |
|
tags: |
|
- not-for-all-audiences |
|
--- |
|
|
|
# LUNA-ProACT - PROtective Analysis for Cyber Threats |
|
|
|
LUNA-ProACT is a context-aware machine learning model designed to protect users from online threats, primarily focusing on cybergrooming. It is created to work in association with LUNA, an AI-powered cybergrooming prevention application. |
|
|
|
LUNA-ProACT uses natural language processing (NLP) to analyze language use in real-time and detects unusual patterns that could indicate potential online threats. It operates locally on iOS and Android mobile devices using TensorFlow Lite, providing real-time protection without requiring network traffic. |
|
|
|
This model results from a collective effort during the TRUE CRIME HACKATHON 2023. Special thanks go to the Polizei Niedersachsen for inspiring the LUNA Cybergrooming Prevention App idea. |
|
|
|
## Key Features |
|
|
|
- **Real-Time Analysis:** LUNA-ProACT scans text input on the fly, examining for patterns and language use typically associated with cyber threats. |
|
- **Context Awareness:** Recognizes cultural, geographical, and age-specific contexts for accurate and relevant threat detection. |
|
- **Local Processing:** Employs TensorFlow Lite to analyze data directly on the user's device, ensuring maximum privacy. |
|
|
|
## Dependencies |
|
|
|
- Python 3.7+ |
|
- TensorFlow 2.5.0 |
|
- HuggingFace Transformers |
|
|
|
## Usage |
|
|
|
1. **Installation:** Import the LUNA-ProACT model into your Python project. |
|
|
|
```python |
|
from transformers import AutoTokenizer, TFAutoModel |
|
tokenizer = AutoTokenizer.from_pretrained("LUNA-ProACT") |
|
model = TFAutoModel.from_pretrained("LUNA-ProACT") |
|
``` |
|
|
|
2. **Inference:** Use the model for threat detection. |
|
|
|
```python |
|
input_text = "Your text here..." |
|
inputs = tokenizer.encode(input_text, return_tensors='tf') |
|
outputs = model(inputs)[0] |
|
|
|
# Outputs return the likelihood of the text being a potential cyber threat. |
|
threat_probability = tf.sigmoid(outputs) |
|
|
|
if threat_probability > 0.5: |
|
print("Potential cyber threat detected!") |
|
``` |
|
|
|
## About Us |
|
|
|
LUNA-ProACT has been released by **Phichayut 'Florentin' Sakwiset** from [WeMake](https://wemake.cx), with contributions from **Leon Lukaszewski**, **Lisa Adolf** & **Klemens Karboswki**. |
|
|
|
## License |
|
|
|
LUNA-ProACT is the property of the Polizei Niedersachsen. It is licensed under the GNU Affero General Public License (AGPL) Version 3 and is available for non-commercial use as an open-source project. |
|
|
|
## Contact Us |
|
|
|
## For any further information or inquiries, please reach us at [[email protected]](mailto:[email protected]). |
|
|
|
### ๐ Thanks to the Polizei Niedersachsen |
|
|
|
We appreciate the platform provided by Polizei Niedersachsen through the TRUE CRIME HACKATHON 2023, which played a crucial role in the inception and development of LUNA-ProACT. |