Big Picture on Privacy Enhancing Technologies in e-Health: A Holistic Personal Privacy Workflow

• Main Authors: Stefan Becher, Armin Gerl, Bianca Meier, Felix Bölz
• Format: Article
• Language: English
• Published: MDPI AG 2020-07-01
• Series: Information
• Subjects: formal languages; GDPR; privacy enhancing technologies; privacy languages
• Online Access: https://www.mdpi.com/2078-2489/11/7/356

The collection and processing of personal data offers great opportunities for technological advances, but the accumulation of vast amounts of personal data also increases the risk of misuse for malicious intentions, especially in health care. Therefore, personal data are legally protected, e.g., by the European General Data Protection Regulation (GDPR), which states that individuals must be transparently informed and have the right to take control over the processing of their personal data. In real applications privacy policies are used to fulfill these requirements which can be negotiated via user interfaces. The literature proposes privacy languages as an electronic format for privacy policies while the users privacy preferences are represented by preference languages. However, this is only the beginning of the personal data life-cycle, which also includes the processing of personal data and its transfer to various stakeholders. In this work we define a personal privacy workflow, considering the negotiation of privacy policies, privacy-preserving processing and secondary use of personal data, in context of health care data processing to survey applicable Privacy Enhancing Technologies (PETs) to ensure the individuals’ privacy. Based on a broad literature review we identify open research questions for each step of the workflow.