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Towards a Privacy Compliant Research Interface for Multicenter Medical Data

: Appenzeller, Arno

Fulltext urn:nbn:de:0011-n-6086869 (305 KByte PDF)
MD5 Fingerprint: 4fd4bed20aa7ee649e3efb296925cc03
Created on: 17.11.2020

Beyerer, Jürgen (Ed.); Zander, Tim (Ed.):
Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory 2019. Proceedings : July, 29 to August, 2, 2019, Triberg-Nussbach, Germany
Karlsruhe: KIT Scientific Publishing, 2020 (Karlsruher Schriften zur Anthropomatik 45)
ISBN: 978-3-7315-1028-4
DOI: 10.5445/KSP/1000118012
Fraunhofer Institute of Optronics, System Technologies and Image Exploitation and Institute for Anthropomatics, Vision and Fusion Laboratory (Joint Workshop) <2019, Triberg-Nussbach>
Conference Paper, Electronic Publication
Fraunhofer IOSB ()

Big Data analysis gains more and more interest in the processing of e-Health data. The potentially big benefit of those analyses comes with a set of new unknown impacts to an individual’s privacy. Still it is important to find a balance between privacy impact and utility of the medical data analysis. To achieve this, this technical report takes a look on different privacy preserving techniques, that could be used for a privacy preserving research interface for medical data. The three techniques Differential privacy, k-Anonymity and Secure multi-party Computation are evaluated on their feasibility for a medical use-case. With those preliminaries some formal definitions are made for a privacy preserving research interface which implements an hybrid approach of the three techniques and a consent based interface.