PAMOLA STUDIO

PAMOLA is an advanced privacy-enhancing studio designed to facilitate secure data management, anonymization, synthetic data generation, and attack risk simulation. It is built on DataHub and integrates state-of-the-art privacy-preserving technologies.

PAMOLA Documentation

• Introduction to PAMOLA
  • What is PAMOLA?
  • Who is PAMOLA for?
  • How Does PAMOLA Work?
• PAMOLA Architecture
  • Overview of PAMOLA’s Architecture
• PAMOLA System Guide
  • System Requirements
  • Deployment via Docker
  • Configuring DataHub for PAMOLA
  • User & Workspace Management
  • Monitoring & Logs
  • Shutting Down PAMOLA
  • Next Steps
• PAMOLA User Guide
  • Getting Started with PAMOLA
  • Managing Datasets
  • Creating Privacy Projects and Pipelines
  • Evaluating Data Privacy & Generating Metrics
  • Running Attack Simulations
  • Extracting Metadata & Reports
  • Next Steps
• PAMOLA Developer Guide
  • Overview of PAMOLA API
  • Using PAMOLA CORE (Python)
  • Next Steps
• Security & Privacy Modeling
  • Overview of Security & Privacy Modeling