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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