🔒 Privacy & Security Demo

Experience cutting-edge Fully Homomorphic Encryption (FHE) technology that enables computation on encrypted therapy data without ever exposing sensitive information.

Why Privacy Matters in Therapy

✓ Patient Trust: Complete confidentiality builds stronger therapeutic relationships
✓ Legal Compliance: HIPAA and GDPR compliant data processing
✓ Research Ethics: Enable studies while protecting individual privacy
✓ Data Security: Military-grade encryption for all sensitive information

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Zero-Knowledge Processing

Analyze data without seeing it

🔒 Fully Homomorphic Encryption Demo

Perform computations on encrypted data without ever decrypting it. This demo simulates FHE operations for privacy-preserving therapy data analysis.

Setup Operation

Operation Type

Input 1 (Patient Score)

Input 2 (Baseline)

Privacy Note: All computations are performed on encrypted data. The raw values are never exposed during processing.

Operation History

No operations performed yet. Try executing an FHE operation above.

Performance Benchmarks

Run some operations to see performance comparisons.

💡 Why FHE Matters for Therapy Data

• Privacy-Preserving Analytics: Analyze patient data without seeing raw values
• Secure Multi-Party Computation: Multiple therapists can collaborate on insights
• Regulatory Compliance: HIPAA-compliant processing of sensitive health data
• Research Applications: Enable large-scale studies while protecting individual privacy

How Fully Homomorphic Encryption Works

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1. Encrypt Data

Patient therapy data is encrypted using advanced mathematical techniques, making it completely unreadable while preserving its computational structure.

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2. Compute Encrypted

Perform complex analytics, machine learning, and statistical analysis directly on the encrypted data without ever decrypting it.

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3. Decrypt Results

Only the final analysis results are decrypted, revealing insights while keeping all individual patient data completely private.

🏥 Clinical Applications

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Multi-Site Research: Collaborate across institutions without sharing raw patient data

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Population Analytics: Analyze trends across patient populations while maintaining privacy

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Outcome Prediction: Build predictive models without exposing individual records

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Quality Assurance: Monitor treatment effectiveness while protecting patient identity

🔬 Research Benefits

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Larger Sample Sizes: Combine datasets from multiple sources securely

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Cross-Border Studies: International collaboration without data transfer restrictions

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Longitudinal Analysis: Track patient progress over time while maintaining anonymity

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Algorithm Development: Train AI models on sensitive data without privacy concerns

Technical Specifications

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Encryption Scheme

Microsoft SEAL with BFV/CKKS schemes

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Security Level

128-bit security with lattice-based cryptography

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Performance

Optimized for real-time therapy applications

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Compatibility

WebAssembly for cross-platform support

Compliance & Standards

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HIPAA Compliant

Full compliance with healthcare privacy regulations

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GDPR Ready

European data protection regulation compliance

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SOC 2 Type II

Enterprise-grade security and availability controls

⚡ Performance Considerations

Trade-offs

• Computation Overhead: 100-1000x slower than plaintext operations
• Memory Usage: Encrypted data requires more storage space
• Network Bandwidth: Larger data packets for encrypted transmission

Optimizations

• Batching: Process multiple values simultaneously
• Caching: Reuse computed intermediate results
• Parallel Processing: Distribute computations across cores

Experience Privacy-First Therapy Technology

Join the future of therapy where patient privacy and data utility coexist seamlessly through advanced cryptographic techniques.