Modelling GDPR-compliance based on Defeasible Logic Reasoning: Insights from Time Complexity Perspective^*

The General Data Protection Regulation (GDPR), an EU data protection law, requires compliance modeling techniques to help service providers meet its stringent requirements. Traditional privacy modeling techniques often fail to address and mitigate threats of non-compliance. This paper introduces an efficient threat modeling technique based on Defeasible Logic Programming (DeLP) to identify and mitigate non-compliance threats. To achieve this, we construct a DeLP-based knowledge base that integrates facts and rules derived from GDPR requirements. We then implement an inference engine to reason about GDPR non-compliance threats upon this knowledge base. Two novel concepts, namely the horizontal complexity and vertical complexity of a DeLP knowledge base, have been defined to further analyze and evaluate the complexity of the proposed DeLP-based modeling mechanism. An empirical demonstration validates the system’s feasibility and confirms the time complexity of the proposed reasoner. The findings demonstrate that the proposed DeLP-based technique provides an effective approach to GDPR compliance modeling and improves legal reasoning.