The principles, methods, algorithms and data structures underlying the ARX anonymization tool have been published in peer-reviewed journals and conference proceedings:
- Carolin EM Koll, Sina M Hopff, Thierry Meurers, Chin Huang Lee, Mirjam Kohls, Christoph Stellbrink, Charlotte Thibeault, Lennart Reinke, Sarah Steinbrecher, Stefan Schreiber, Lazar Mitrov, Sandra Frank, Olga Miljukov, Johanna Erber, Johannes C Hellmuth, Jens-Peter Reese, Fridolin Steinbeis, Thomas Bahmer, Marina Hagen, Patrick Meybohm, Stefan Hansch, István Vadász, Lilian Krist, Steffi Jiru-Hillmann, Fabian Prasser, Jörg Janne Vehreschild & NAPKON Study Group.
Statistical biases due to anonymization evaluated in an open clinical dataset from COVID-19 patients.
Sci Data. 2022 Dec 21;9(1):776. (DOI)
- Anna C Haber, Ulrich Sax, Fabian Prasser, NFDI4Health Consortium
Open Tools for Quantitative Anonymization of Tabular Phenotype Data: Literature Review
Brief Bioinformatics. bbac440 (2022). (DOI)
- Thierry Meurers, Raffael Bild, Kieu-Mi Do, and Fabian Prasser.
A Scalable Software Solution for Anonymizing High-Dimensional Biomedical Data.
GigaScience. 2021 Oct;10(10):giab068. (DOI)
- Carolin EM Jakob, Florian Kohlmayer, Thierry Meurers, Jörg Janne Vehreschild, and Fabian Prasser.
Design and Evaluation of a Data Anonymization Pipeline to Promote Open Science on COVID-19.
Sci Data. 2020 Dec 10;7(1):1-0. (DOI)
- Fabian Prasser, Johanna Eicher, Helmut Spengler, Raffael Bild, Klaus A. Kuhn.
Flexible Data Anonymization Using ARX — Current Status and Challenges Ahead.
J Software Pract Exper 50, 7 (2020);1277-1304. (DOI)
- Johanna Eicher, Raffael Bild, Helmut Spengler, Klaus A. Kuhn, Fabian Prasser.
A Comprehensive Tool for Creating and Evaluating Privacy-Preserving Biomedical Prediction Models.
BMC Med Inform Decis Mak 20, 29 (2020). (DOI)
- Raffael Bild, Johanna Eicher, Fabian Prasser.
Efficient Protection of Health Data from Sensitive Attribute Disclosure.
Proceedings MIE / Studies in Health Technology and Informatics, 270, 193-197 (2020). (DOI)
- Raffael Bild, Klaus A. Kuhn, Fabian Prasser.
Better Safe Than Sorry – Implementing Reliable Health Data Anonymization.
Proceedings MIE / Studies in Health Technology and Informatics, 270, 68-72 (2020). (DOI)
- Helmut Spengler, Fabian Prasser.
Protecting Biomedical Data Against Attribute Disclosure.
Studies in Health Technology and Informatics, German Medical Data Sciences: Shaping Change – Creative Solutions for Innovative Medicine, 2019(267), 207-214. (DOI)
- Fabian Prasser, Helmut Spengler, Raffael Bild, Johanna Eicher, Klaus A. Kuhn.
Privacy-Enhancing ETL-Processes for Biomedical Data.
International Journal of Medical Informatics, 2019(126), 72-81. (DOI)
- Raffael Bild, Klaus A. Kuhn, Fabian Prasser.
SafePub: A Truthful Data Anonymization Algorithm With Strong Privacy Guarantees.
Proceedings on Privacy Enhancing Technologies, 2018(1), 67-87. (DOI)
- Fabian Prasser, James Gaupp, Zhiyu Wan, Weiyi Xia, Yevgeniy Vorobeychik, Murat Kantarcioglu, Klaus A. Kuhn, Bradley A. Malin.
An Open Source Tool for Game Theoretic Health Data De-Identification.
Proceedings of the AMIA 2017 Annual Symposium (AMIA 2017). (Link)
- Johanna Eicher, Klaus A. Kuhn, Fabian Prasser.
An Experimental Comparison of Quality Models for Health Data De-Identification.
Proceedings of the 16th World Congress on Health and Biomedical Informatics (MedInfo 2017). (DOI)
- Fabian Prasser, Florian Kohlmayer, Helmut Spengler, Klaus A. Kuhn.
A Scalable and Pragmatic Method for the Safe Sharing of High-Quality Health Data.
IEEE Journal of Biomedical and Health Informatics, March 2017. (DOI)
- Fabian Prasser, Johanna Eicher, Raffael Bild, Helmut Spengler, Klaus A. Kuhn.
A Tool for Optimizing De-Identified Health Data for Use in Statistical Classification.
Proceedings of the 30th IEEE International Symposium on Computer-Based Medical Systems, June 2017, Thessaloniki, Greece.
(DOI)
- Fabian Prasser, Raffael Bild, Johanna Eicher, Helmut Spengler, Florian Kohlmayer, Klaus A. Kuhn.
Lightning: Utility-Driven Anonymization of High-Dimensional Data.
Transactions on Data Privacy 9:2 (2016) 161 – 185, August 2016. (Link)
- Fabian Prasser, Raffael Bild, Klaus A. Kuhn.
A Generic Method for Assessing the Quality of De-Identified Health Data.
Proceedings of MIE 2016 / Studies in Health Technology and Informatics, Volume 228: Exploring Complexity in Health: An Interdisciplinary Systems Approach, IOS Press, August 2016. (DOI)
- Fabian Prasser*, Florian Kohlmayer*, Klaus A. Kuhn.
The Importance of Context: Risk-Based De-Identification of Biomedical Data.
Methods of Information in Medicine, Schattauer, June 2016. (DOI)
- Fabian Prasser, Florian Kohlmayer, Klaus A. Kuhn.
Efficient and Effective Pruning Strategies for Health Data De-Identification.
BMC Medical Informatics and Decision Making, April 2016. (DOI)
- Fabian Prasser*, Florian Kohlmayer*.
Putting Statistical Disclosure Control Into Practice: The ARX Data Anonymization Tool.
In: Gkoulalas-Divanis, Aris, Loukides, Grigorios (Eds.): Medical Data Privacy Handbook, Springer, November 2015. ISBN: 978-3-319-23632-2. (DOI)
- Florian Kohlmayer*, Fabian Prasser*, Klaus A. Kuhn.
The Cost of Quality: Implementing Generalization and Suppression for Anonymizing Biomedical Data With Minimal Information Loss.
Journal of Biomedical Informatics, October 2015. (DOI)
- Fabian Prasser*, Florian Kohlmayer*, Ronald Lautenschlaeger, Klaus A. Kuhn.
ARX – A Comprehensive Tool for Anonymizing Biomedical Data.
Proceedings of the AMIA 2014 Annual Symposium, November 2014, Washington D.C., USA. (Pubmed)
- Fabian Prasser*, Florian Kohlmayer*, Klaus A. Kuhn.
A Benchmark of Globally-Optimal Anonymization Methods for Biomedical Data.
Proceedings of the 27th IEEE International Symposium on Computer-Based Medical Systems, May 2014, New York City, USA. (DOI)
- Florian Kohlmayer*, Fabian Prasser*, Claudia Eckert, Klaus A. Kuhn.
A Flexible Approach to Distributed Data Anonymization.
Journal of Biomedical Informatics, December 2013. (DOI)
- Florian Kohlmayer*, Fabian Prasser*, Claudia Eckert, Alfons Kemper, Klaus. A. Kuhn.
Flash: Efficient, Stable and Optimal K-Anonymity.
Proceedings of the 4th IEEE International Conference on Information Privacy, Security, Risk and Trust (PASSAT), September 3 – 5, 2012, Amsterdam, Netherlands. (DOI)
- Florian Kohlmayer*, Fabian Prasser*, Claudia Eckert, Alfons Kemper and Klaus A. Kuhn.
Highly Efficient Optimal K-Anonymity For Biomedical Datasets.
Proceedings of the 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS), June 2012. (DOI)
* Both authors contributed equally to this work.