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Data Protection by Design Tool for Automated GDPR Compliance Verification Based on Semantically Modeled Informed Consent

  • Tek Raj Chhetri*
  • , Anelia Kurteva
  • , Rance J. Delong
  • , Rainer Hilscher
  • , Kai Korte
  • , Anna Fensel
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The enforcement of the GDPR in May 2018 has led to a paradigm shift in data protection. Organizations face significant challenges, such as demonstrating compliance (or auditability) and automated compliance verification due to the complex and dynamic nature of consent, as well as the scale at which compliance verification must be performed. Furthermore, the GDPR’s promotion of data protection by design and industrial interoperability requirements has created new technical challenges, as they require significant changes in the design and implementation of systems that handle personal data. We present a scalable data protection by design tool for automated compliance verification and auditability based on informed consent that is modeled with a knowledge graph. Automated compliance verification is made possible by implementing a regulation-to-code process that translates GDPR regulations into well-defined technical and organizational measures and, ultimately, software code. We demonstrate the effectiveness of the tool in the insurance and smart cities domains. We highlight ways in which our tool can be adapted to other domains.

Original languageEnglish
Article number2763
JournalSensors
Volume22
Issue number7
DOIs
Publication statusPublished - 3 Apr 2022

Bibliographical note

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • compliance verification
  • data protection by design
  • data sharing
  • distributed systems
  • GDPR
  • informed consent
  • knowledge graph
  • privacy
  • standard data protection model

ASJC Scopus subject areas

  • Analytical Chemistry
  • Information Systems
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering

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