![]() 6 concludes the paper and provides directions for future work. ![]() ![]() Section 5 illustrates PE-BPMN application and development. 3 overviews the PET classification, which is used to describe PE-BPMN in Sect. The rest of the paper is structured as follows: in Sect. Feasibility of PE-BPMN is illustrated using the mobile application scenario where emergency data are gathered using a mobile phone app. Based on the PET classification, we propose PE-BPMN – a BPMN extension with privacy enhancing technologies and characterize the goals of using PETs. We consider how business process model and notation (BPMN) could support analysis of private data leakage. The PETs are applied to enforce privacy requirements. should not leak to the officer or any other unintended party. For example, if a bank officer generates a report about the payment transactions, data about the payer, recipient, etc. In this paper, we primarily focus on privacy analysis in the honest-but-curious adversary cases. However, little is done to assess privacy properties within business processes, or to address unintentional privacy leakages when some input data objects or derived data objects are sent to other parties. There exist regulatory standards (e.g., ) and approaches (e.g., ) for risk-oriented privacy management. Organisations wishing to cope with new restrictions or to deploy new privacy enhancing technologies (PETs), need to understand the privacy properties and assumptions of their current and newly developed systems. Furthermore, companies are starting to use privacy as a sales argument, e.g., adding differential privacy to their services . A new General Data Protection Regulation is entering into force in EU and the new Privacy Shield agreement will be affecting businesses in US with restrictions compared to the Safe Harbour agreement . The importance of privacy is continuously growing.
0 Comments
Leave a Reply. |