Project "PrivacyUmbrella"

Smart health: ensuring data privacy by providing comprehensive anonymization processes

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Thanks to wearable technology, “smart health” has become an essential element of modern life for many people.

Thanks to the constant development of communication technology, such as portable mobile devices and wearables, the concept of “smart health” - and with it the continuous improvement of personal health - has become an essential element of modern life for many people. Through the constant collection of data, smart health can promote a healthier lifestyle and also be used to identify possible issues. For example, this technology might lead to a patient starting treatment early or at least in good time.

However, as health data becomes more detailed and accessible to multiple parties, it also becomes vulnerable to attacks on individual patients’ privacy. In order to account for the particular privacy concerns relating to personal medical data, the objective of this project is to develop highly specialized anonymization solutions based on modern data analysis.

The main challenge of this project will be to combine multiple, previously isolated methods into a single integrated open-source demonstrator, and to show that the anonymization capabilities (privacy metrics) of the individual methods can be maintained while also deriving a holistic, combined concept of privacy or anonymization. The project team will focus in particular on identifying and optimizing anonymization combinations, embedding these methods in existing open-source systems, and using machine learning to assess their vulnerability.

The consortium

This interdisciplinary project consortium, led by Fraunhofer ITEM, has many years’ experience relating to the secure evaluation of medical data in compliance with data protection regulations. Here is an overview of the relevant preliminary work, as well as the infrastructure required for the secure storage and evaluation of personal data.

Preliminary work at Fraunhofer ITEM

  • Lena Wiese, Tim Waage and Michael Brenner. CloudDBGuard: A Framework for encrypted data storage in NoSQL Wide Column Stores. Data and Knowledge Engineering. Elsevier, 2020.
  • Ferdinand Bollwein and Lena Wiese. Keeping Secrets by Separation of Duties while Minimizing the Amount of Cloud Servers. Transactions on Large-scale Data and Knowledge-Centered Systems. Springer, 2018
  • Ferdinand Bollwein and Lena Wiese. On the Hardness of Separation of Duties Problems for Cloud Databases. TrustBus. Springer, 2018.
  • Ferdinand Bollwein, Lena Wiese. Closeness Constraints for Separation of Duties in Cloud Databases as an Optimization Problem. BICOD 2017: 133-145. Springer, 2017. 

Preliminary work at the University Medical Center Mainz

  • MIRACUM: This project brings together ten university hospitals, two universities and one industry partner from seven German states.
  • Mainzelliste: Web-based service for pseudonymization, fiduciary storage of identity data and record linkage.
  • Riegel J, Ben Amor M, Brenner T, Drepper J, Franke M, Grün M, Hamacher K, Hund H, Knopp C, Kussel T, Lemmer M, Parciak M, Rahm E, Rohde F, Sax U, Schepers J, Sehili Z, Suhr M, Panholzer T, Lablans M. Chancen von Open-Source-Software am Beispiel der Pseudonymisierungslösung "Mainzelliste". 2021 doi: 10.3205/20gmds204
  • Lablans, M., Borg, A., Ückert, F. A RESTful interface to pseudonymization services in modern web applications. BMC medical informatics and decision making. 2015; 15(1), 1-10.

Preliminary work at University Hospital Frankfurt

  • Schaaf, J., Sedlmayr, M., Schaefer, J., & Storf, H. (2020). Diagnosis of Rare Diseases: a scoping review of clinical decision support systems. Orphanet journal of rare diseases, 15(1), 1-14.
  • Storf, H., Stausberg, J., Kindle, G., Quadder, B., Schlangen, M., Walter, M. C., ... & Wagner, T. O. (2020). Patient registries for rare diseases in Germany: Concept paper of the NAMSE strategy group. Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz, 63(6), 761-770.
  • Storf, H., Schaaf, J., Kadioglu, D., Göbel, J., Wagner, T. O., & Ückert, F. (2017). Register für seltene Erkrankungen. Bundesgesundheitsblatt-Gesundheitsforschung-Gesundheitsschutz, 60(5), 523-531.

Preliminary work at MCS Datalabs

  • Scherrer A, Zimmermann T, Riedel S, Mousa F, Wasswa-Musisi I, Zifrid R, Tillil. H, Ulrich P, Kosmidis T, Reis J, Oestreicher G, Möhler M, Kalamaras I, Votis K, Venios S, Plakia M, Diamanopoulos S. (2022). Digitally assisted planning and monitoring of supportive recommendations in cancer patients. In: Maglogiannis I, Iliadis L, Macintyre J, Cortez P (eds). Artificial Intelligence Appliations and Innovations. AIAI 2022 IFIP WG 12.5 International Workshops. AIAI 2022. IFIP Advances in Information and Communication Technology, vol 652. Springer, Cham, pp 401-411. DOI: 10.1007/978-3-031-08341-9_32

Your contact person

Lena Wiese

Contact Press / Media

Prof. Dr. Lena Wiese

Manager of the Working Group on Bioinformatics/Head of Attract Group Bioinformatics “IDA – intelligent data analysis for good health and chemical safety“

Phone +49 511 5350-303