Privacy-enhanced BPMN: enabling data privacy analysis in business processes models

Abstract

Privacy-enhancing technologies play an important role in preventing the disclosure of private data as information is transmitted and processed. Although business process model and notation (BPMN) is well suited for expressing stakeholder collaboration and business processes support by technical solutions, little is done to depict and analyze the flow of private information and its technical safeguards as it is disclosed to process participants. This gap motivates the development of privacy-enhanced BPMN (PE-BPMN)—a BPMN language for capturing PET-related activities in order to study the flow of private information and ease the communication of privacy concerns and requirements among stakeholders. We demonstrate its feasibility in a mobile app scenario and present techniques to analyze information disclosures identified by models enriched with PE-BPMN.