DetaBord Methodological Foundations Overview

While DetaBord started as a platform for privacy-preserving machine learning with Differential Privacy (DP), DetaBord does not rely on DP as such but is – as a platform for trustworthy analytics and Ethical AI – rather method and technology agnostic.

Privacy preserving technologies that are already integrated or on the roadmap for DetaBord are:

  • Differential Private Machine Learning
  • Differential Private SQL / Data Analysis
  • Private Synthetic Data
  • Federated Learning
  • Federated Private SQL
  • Homomorphic Encryption
  • Secure Multi Party Computation
  • Privacy Preserving Data Linkage
  • Data Masking and Governance
  • Data Lineage, Tracability and Audits
  • Ethical AI Processes

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