Security and Privacy of the Data Science Knowledge Graph – SecureKG

Problem:

• Large-scale multidisciplinary distributed scenarios
• Security, privacy and accountability challenges on the diverse and heterogeneous data sets whose lineage is managed by the Renga platform.
• Strict legal landscapes (e.g., LPD, EU GDPR) also call for stronger protection for personal data.

Solution:

Blockchain-based tech for federated self-sovereign identities, decentralized logging and access control:

• Consistency, integrity and accountability: blockchain-based immutable and traceable logging
• Multi-level access control with federated identity: distributed access rights and consensus rules
• Confidentiality and privacy protection: collective homomorphic encryption, and query auditing for inference-resistance
• Configurable and modular architecture, adaptable to the domain requirements

Impact:

Key enabler for effective, secure, privacy-conscious and data protection-compliant provenance for distributed data science.