PIPE - Pseudonymization of Information for Privacy in e-Health

  • Ettmayer, Klaus (Researcher)
  • Grün, Katharina (Researcher)
  • Karlinger, Michael (Researcher)
  • Nitsche, Georg (Researcher)
  • Schrefl, Michael (PI)

Project: Funded researchFederal / regional / local authorities

Project Details

Description

The discussion of privacy is one of the fundamental issues in health care today and a trade-off between the patients' requirement for privacy as well as the society's needs for improving efficiency and reducing costs of the health care system. Today, highly sensitive data is managed in medical systems that are however hardly protected. As a result of the high sensitivity of medical data and due to an endless list of security breaches revealing patients' data, there is an increasing social and political pressure to prevent the misuse of health data. Project PIPE (Pseudonymization of Information for Privacy in e-Health) aims at developing techniques that make it technically impossible to violate the privacy of health care consumers. The objective of the project is to develop a secure, configurable pseudonymization service that can be employed for and customized to different e-health applications. Its main idea is to disassociate personal identification data from electronic health records and to control access to sensitive identification data via a layered encryption model. By pseudonymizing electronic health records, PIPE provides secondary use of medical data without revealing the patients' identity.
StatusFinished
Effective start/end date01.08.200828.02.2011

Collaborative partners

  • Johannes Kepler University Linz (lead)
  • Secure Business Austria (Project partner)
  • Technische Universität Wien, Institut für Softwaretechnik und interaktive multimediale Systeme (Project partner)
  • GenoSense Diagnostics GmbH (Project partner)
  • Braincon Technologies GmbH (Project partner)

Fields of science

  • 102 Computer Sciences
  • 102030 Semantic technologies
  • 502050 Business informatics
  • 102010 Database systems
  • 102035 Data science
  • 502058 Digital transformation
  • 503008 E-learning
  • 509026 Digitalisation research
  • 102033 Data mining
  • 102027 Web engineering
  • 102028 Knowledge engineering
  • 102016 IT security
  • 102015 Information systems
  • 102025 Distributed systems

JKU Focus areas

  • Digital Transformation