🛡️ PII-Shield

Your Intelligent Guardian for Personal Data Protection

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🌟 What is PII-Shield?

PII-Shield is your cutting-edge solution for protecting sensitive information in text data. Powered by advanced transformer architecture, it's your first line of defense against unintended PII exposure.

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🎯 Core Capabilities

🔍 Smart Detection

"Regular text with sarah.smith@email.com" → "Regular text with [EMAIL_1]"

🎭 Intelligent Masking

"Call John at (555) 123-4567" → "Call [PERSON_1] at [PHONE_1]"

📊 Structured Mapping

Original → Masked → JSON Mapping

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🚀 Model Architecture

🧠 Two-Stage Intelligence

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⚡ Supported PII Categories

Category	Icon	Example
Names	👤	John Smith
Emails	📧	user@domain.com
Phones	📱	(555) 123-4567
Addresses	🏠	123 Privacy St
SSN	🔢	XXX-XX-XXXX
Credit Cards	💳	XXXX-XXXX-XXXX
DOB	📅	MM/DD/YYYY
IPs	🌐	192.168.1.1

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💫 How It Works

🎯 Detection Phase

def detect_pii(text: str) -> List[Entity]:
    """
    🔍 Intelligent PII detection
    Returns list of identified entities
    """
    pass

🎭 Masking Phase

def mask_pii(text: str, entities: List[Entity]) -> Dict:
    """
    🛡️ Smart PII masking
    Returns masked text and mapping
    """
    pass

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🎮 Input/Output

📥 Input Format

{
    "text": "Your sensitive text here",
    "options": {
        "mask_format": "[TYPE_INDEX]",
        "return_mapping": true
    }
}

📤 Output Format

{
    "masked_text": "Your [TYPE_1] text here",
    "pii_mapping": [
        {
            "label": "TYPE",
            "value": "sensitive",
            "index": 1
        }
    ]
}

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🚦 Performance Stats

Metric	Score	Trend
Precision	98.5%	⬆️
Recall	97.8%	⬆️
Speed	2ms/req	⬇️
Accuracy	99.1%	➡️

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🛠️ Technical Requirements

• 🖥️ CUDA-capable GPU
• 💾 8GB+ VRAM
• 🐍 Python 3.8+
• 🔧 PyTorch 2.0+

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🔒 Security First

🎯 Best Practices

1. 🔐 Never store raw PII
2. 💾 Process in-memory only
3. 🧹 Clear cache regularly
4. 📝 Enable access logging
5. 🔄 Regular updates

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⚠️ Known Limitations

• 📏 Max 2048 tokens
• 🗣️ English-primary
• 💡 Domain adaptation needed
• 💾 GPU memory bound

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📜 License

Apache License 2.0 • Made with ❤️ for Privacy

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🤝 Support & Community

• 💬 LinkedIn
• 📧 Email Support