| --- |
| language: |
| - en |
| - de |
| --- |
| |
| # 🛡️ MLP Cybersecurity Classifier |
|
|
| This repository hosts a lightweight `scikit-learn`-based MLP classifier trained to distinguish cybersecurity-related content from other text, using sentence-transformer embeddings. It supports English and German input texts. |
|
|
| ## 📊 Training Data |
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| The model was trained on a multilingual dataset of cybersecurity and non-cybersecurity news articles. The dataset is publicly available on Zenodo: |
| 🔗 [https://zenodo.org/records/16417939](https://zenodo.org/records/16417939) |
|
|
| ## 📦 Model Details |
|
|
| - **Architecture**: `MLPClassifier` with hidden layers `(128, 64)` |
| - **Embedding model**: [`intfloat/multilingual-e5-large`](https://huggingface.co/intfloat/multilingual-e5-large) |
| - **Input**: Cleaned article (removed stopwords) or report text |
| - **Output**: Binary label (e.g., `Cybersecurity`, `Not Cybersecurity`) |
| - **Languages**: English, German |
|
|
| ## 🔧 Usage |
|
|
| ```python |
| from sentence_transformers import SentenceTransformer |
| from huggingface_hub import hf_hub_download |
| import joblib |
| |
| # 1. Load the embedding model |
| embedder = SentenceTransformer("intfloat/multilingual-e5-large") |
| |
| # 2. Load the pretrained MLP classifier from Hugging Face Hub |
| model_path = hf_hub_download(repo_id="selfconstruct3d/cybersec_classifier", filename="cybersec_classifier.pkl") |
| model = joblib.load(model_path) |
| |
| # 3. Example input texts (can be in English or German) |
| texts = [ |
| "A new ransomware attack has affected critical infrastructure in Germany.", |
| "The local sports club hosted its annual summer festival this weekend." |
| ] |
| |
| # 4. Generate embeddings |
| embeddings = embedder.encode(texts, convert_to_numpy=True, show_progress_bar=False) |
| |
| # 5. Predict cybersecurity relevance |
| predictions = model.predict(embeddings) |
| |
| # 6. Output results |
| for text, label in zip(texts, predictions): |
| print(f"Text: {text}\nPrediction: {label}\n") |
| |
| ``` |
|
|
|
|
| ## Licence |
| This model is licensed for non-commercial use only (CC BY-NC 4.0). |
| For commercial inquiries, please contact dzenan.hamzic@ait.ac.at. |
