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language: |
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- de |
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pipeline_tag: text-classification |
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--- |
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# LUNA-ProACT - PROtective Analysis for Cyber Threats |
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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. |
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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. |
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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. |
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## Key Features |
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- **Real-Time Analysis:** LUNA-ProACT scans text input on the fly, examining for patterns and language use typically associated with cyber threats. |
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- **Context Awareness:** Recognizes cultural, geographical, and age-specific contexts for accurate and relevant threat detection. |
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- **Local Processing:** Employs TensorFlow Lite to analyze data directly on the user's device, ensuring maximum privacy. |
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## Dependencies |
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- Python 3.7+ |
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- TensorFlow 2.5.0 |
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- HuggingFace Transformers |
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## Usage |
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1. **Installation:** Import the LUNA-ProACT model into your Python project. |
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```python |
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from transformers import AutoTokenizer, TFAutoModel |
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tokenizer = AutoTokenizer.from_pretrained("LUNA-ProACT") |
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model = TFAutoModel.from_pretrained("LUNA-ProACT") |
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``` |
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2. **Inference:** Use the model for threat detection. |
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```python |
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input_text = "Your text here..." |
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inputs = tokenizer.encode(input_text, return_tensors='tf') |
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outputs = model(inputs)[0] |
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# Outputs return the likelihood of the text being a potential cyber threat. |
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threat_probability = tf.sigmoid(outputs) |
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if threat_probability > 0.5: |
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print("Potential cyber threat detected!") |
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``` |
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## About Us |
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LUNA-ProACT has been released by **Phichayut 'Florentin' Sakwiset** from WE-MAKE.IO, with contributions from **Leon Lukaszewski**, **Lisa Adolf** & **Klemens Karboswki**. |
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## License |
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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. |
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Please see the [LICENSE (TBA)](LICENSE) file for more details. |
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## Contribution |
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We welcome contributions to help improve LUNA-ProACT. If you have any issues or feature requests, please open a new issue or pull request. |
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Remember to follow our [contribution guidelines](https://huggingface.co/WE-MAKE-IO/LUNA-ProACT/blob/main/CONTRIBUTING.md) to ensure a smooth collaboration process. Thank you for your interest in contributing to LUNA-ProACT. |
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## Contact Us |
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For any further information or inquiries, please reach us at [hey@we-make.io](mailto:hey@we-make.io). |
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[](mailto:hey@we-make.io) |
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--- |
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### 💙 Thanks to the Polizei Niedersachsen |
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*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. |
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Let's work together to make our digital world safer.* |
