Security & Privacy

This section outlines the security posture and privacy considerations taken in the design of this diagnostic prototype. While it does not handle real patient data, the project simulates conditions aligned with HIPAA-like safeguards.

Privacy-First Principles

All inputs to the interactive query tool are processed entirely in-memory. No form data is stored, logged, or transmitted beyond what is needed to return a one-time result. This protects user confidentiality, even in a simulated academic setting.

  • No cookies or session storage
  • No personally identifying information is ever collected
  • All submissions are ephemeral and anonymous

Data Handling and API Scope

The API endpoint that powers predictions is tightly scoped to numeric vectors only: 

{
  "radius_mean": 12.4,
  "texture_mean": 17.1,
  "perimeter_mean": 80.1,
  ...
  "fractal_dimension_worst": 0.086
}

These values carry no patient ID, timestamp, or system metadata. Requests are parsed, evaluated, and discarded within the same runtime cycle.

Deployment Environment

The model is hosted on a local Flask server in demo mode. For any real-world deployment, the following precautions would be required:

TLS/HTTPS Encryption

All traffic would be encrypted in transit using modern ciphers.

Firewall Restrictions

Endpoints would be accessible only within trusted network boundaries.

Audit Logging (Optional)

Anonymized logs could be retained only with explicit opt-in.

No External Dependencies

The backend uses only local computation and avoids third-party calls.

Future Compliance Features

If this project were to be extended into a production setting, several compliance pathways would need to be followed:

  • HIPAA or GDPR data protection policies
  • Secure cloud deployment with access controls
  • Signed consent for any stored diagnostic data
  • Audit logs and traceability for all prediction events

These concerns were not implemented in the scope of this academic project, but the design accommodates future integration.

Key Takeaways

  • This interface does not collect or store any user data or identifiers.
  • All inputs are used solely for real-time prediction and discarded immediately.
  • Security principles like isolation, minimal scope, and encryption are baked into the architecture.