Anonymization Ontology: A Privacy-Preserving Framework for GDPR Compliant Anonymization of Personal Health Data

Abstract

Anonymization ontology describes generic anonymization software to achieve GDPR-compliant anonymization. We semantically model the anonymization process as a modular software design to allow easy integration of new privacy methods and data from diverse data domains. It provides a common vocabulary for processes within the privacy preservation domain. The ontology models the concepts, data types, and algorithms used in the anonymization process. It captures the relationships between data attributes,their attributes types, and the algorithms that can be applied to achieve privacy protection.