Analysing the Design of Privacy-Preserving Data-Sharing Architecture

Abstract

Privacy has become an essential software quality to consider in a software system. Privacy practices should be adopted from the early stages of the system design to safeguard personal data from privacy violations. Privacy patterns are proposed in industry and academia as reusable design solutions to address different privacy issues. However, the diverse types and granularity of the patterns lead to difficulty for the practitioner to select and adopt them in the architecture. First, the fragmented information about the system actors in the patterns does not align with the regulatory entities and interactions between them. Second, these privacy patterns lack architectural perspectives that could help weave patterns into concrete software designs. Third, the consequences of applying the patterns have not covered the impacts on software quality attributes. This thesis aims to provide guidance to software architects and practitioners for considering and applying privacy patterns in their design, by adding new perspectives to the existing patterns. First, the research provides an analysis of the relationships between regulatory entities and their responsibility in adopting the patterns in a software design. Then, the research reports studies that were conducted using architectural-level modelling-based approaches, to analyse the architectural views of privacy patterns. The analyses aim to improve understanding of how privacy patterns are applied in software designs and how such a design affects software quality attributes, including privacy, performance, and modifiability. Finally, in an effort to harmonise and unite the extended view of privacy patterns that have a close relation to system architecture, this research proposes an enhanced pattern catalogue and a systematic privacy-by-design (PbD) pattern-selection model that aims to aid and guide software architects in pattern selection during software design. The enhanced pattern catalogue offers consolidated information on the extended view of privacy patterns. The selection model provides a structured way for the practitioner to know when and how to use the pattern catalogue in the system-design process. Two industry case studies are used to evaluate the proposed pattern catalogue and selection model. The findings demonstrate how the proposed frameworks are applicable to different types of data-sharing software systems and their usability in supporting pattern selection decisions in the privacy design