A Methodology to Validate Compliance to the GDPR

Abstract

This study analyses two state-of-the-art methodologies for eliciting privacy threats in software contexts, LINDDUN and PIA. A first goal is to understand the limitations of these methodologies in terms of compliance to the provisions of the robust General Data Protection Regulation (GDPR). A second goal is to improve the first methodology by addressing its limitations and proving a more complete coverage with regards to the regulation. The study is divided into two phases; an analysis of the current coverage of the two methodologies and the development of an extended version of LINDDUN. The extended LINDDUN includes a privacy-aware Data Flow Diagram and extensions of the Content Unawareness and Policy and Noncompliance threat trees, as well as developed rules for defining where in a software design a privacy threat commonly exists. It was observed that PIA was considered more effective than LINDDUN in identifying design issues related to GDPR. While the extended version of LINDDUN showed to provide a more complete coverage than the original LINDDUN.