SecureKG
Security and Privacy of the Data Science Knowledge Graph
Started
April 1, 2018
Status
Completed
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Abstract
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SDSC Team:
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PI | Partners:
Co-PIs:
- Prof. Jean-Pierre Hubaux (EPFL)
- Prof. Bryan Ford (EPFL)
description
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.
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