Privacy- and Consent-aware Data Sharing with Machine Learning
  The the basic elements of the research work; this will include key objectives of:
-Define an architecture of digital trust and identity integration using a Distributed Ledger.
- Integrate a citizen-controlled consent model for data-sharing attributes.
- Define and implement fine-grained access contract policies based on attributes such as time, location and identity.
- Integrate Homomorphic encryption with data contract binding.
- Implement privacy-aware machine learning.
- Implement the revocation of citizen consent and unlearning machine models.
- Define audit trails for citizen data, and which can only be seen by citizens. Implement the revocation of data within learning models.

  • Start Date:

    1 August 2024

  • End Date:

    31 August 2025

  • Activity Type:

    Externally Funded Research

  • Funder:

    Digital Health Institute

  • Value:

    £23627

Project Team