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

Sensors

Kai Korte¹  Tek Raj Chhetri²  Anelia Kurteva²  Rainer Hilscher²  Anna Fensel²  Rance J. DeLong³ 

[1] Institut für Rechtsinformatik (IRI), Leibniz Universität Hannover, 30167 Hannover, Germany;Semantic Technology Institute (STI), Department of Computer Science, University of Innsbruck, 6020 Innsbruck, Austria;The Open Group, Reading, Berkshire RG1 1AX, UK;

关键词: GDPR;    privacy;    compliance verification;    informed consent;    standard data protection model;    data sharing;   

DOI  :  10.3390/s22072763

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown