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README.md
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ππ€ **Binary URL Classifier with BERT**
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Welcome to our Binary URL Classifier! π
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### What it Does?
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This classifier categorizes URLs into two categories: Good (Non-Malicious) and Bad (Malicious). It uses BERT, a powerful language model, to understand the content and context of URLs for accurate predictions.
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### How it Works?
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1. **Data**: Trained on a curated dataset of good and bad URLs from this repo https://github.com/faizann24/Using-machine-learning-to-detect-malicious-URLs/tree/master?tab=readme-ov-file.
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2. **Training**: Fine-tuned a pre-trained BERT model using Hugging Face's Transformers library.
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3. **Evaluation**: Validation(15%) and Test(15%) set kept Aside.
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4. **Inference**: Provides probability scores for new URLs, indicating their likelihood of being good or bad.
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### Usage π
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1. **Input**: Provide a URL to classify.
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2. **Output**: Receive a probability score for its safety.
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### Why Trust Us? π
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- **Robust Training**: Trained on diverse and representative datasets.
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- **Evaluation**: Rigorously tested for accuracy and reliability.
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- **Simple & Effective**: Empowers users to make informed decisions about URL safety.
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### Let's Make the Web Safer! π
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Our Binary URL Classifier with BERT is here to enhance online safety. Whether you're a security professional, developer, or concerned user, it helps identify malicious URLs for proactive protection.
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Try it now and experience the power of BERT in URL classification! We're open to feedback and suggestions for continuous improvement. Stay safe online! ππ‘οΈ
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