Overview
The volume of sensitive, medically relevant data recorded both in healthcare settings and by smart devices is growing rapidly and must be handled with utmost care. At the same time, AI and Big Data methods enable the efficient processing of such data, paving the way for individualized precision medicine and long-term studies of the effects of medications, therapies, and behaviors. Yet a central question remains: how can the anonymity of the patients behind these data volumes be preserved?
As a catalyst for anonymization research in medical applications, the AnoMed Cluster aims to confront anonymization researchers with the specific challenges of medical use cases, while simultaneously informing medical practitioners about the risks of de-anonymization and the potential of state-of-the-art anonymization techniques.
Objectives
The AnoMed Cluster will investigate new, provably secure, and utility-preserving anonymization solutions for medical applications. For the international research community, it will establish a benchmarking platform that allows researchers to upload and rigorously test their anonymization methods.
This platform will serve as a foundation for the evaluation of various anonymization metrics. It will provide interfaces for medical researchers and industry partners to define gold standards, specify metrics, and securely manage data. Furthermore, a collection of medical application scenarios will be created, enabling stakeholders to interact with medical data and the latest anonymization research results—exploring both protective mechanisms and attack models.
Technology transfer will be accelerated through targeted attacks on medical challenges and a comprehensive science communication campaign. This will make the risks of data misuse tangible for companies, clinicians, and citizens alike, while demonstrating that modern anonymization methods can effectively safeguard against such risks.
Beyond infrastructure development, AnoMed will focus on collaborating with experts from IT security, medicine, AI research, and industry to design novel anonymization approaches tailored to the defined challenge tasks.
A key pillar for accelerating technology transfer, raising user awareness, and evaluating new anonymization concepts is the continuous search for weaknesses, including the development of de-anonymization attacks. The AnoMed Cluster will explicitly design and analyze such attacks to strengthen future defenses.
To ensure a sound understanding of the legal implications of both submitted and internally developed solutions, legal research will be conducted in parallel. This includes analyses and interpretations of GDPR provisions concerning identifiability, anonymity, and pseudonymity of data, thereby contributing to ongoing national discussions and to privacy-by-design approaches in technology development.
Ultimately, the cluster aims to bring the innovation potential and new treatment opportunities enabled by reliable anonymization techniques into medicine and the medical technology industry, thereby advancing public health and economic growth in Germany and across the European Economic Area (EEA).
Contact person for further inquiries:
Prof. Dr. rer. nat. Esfandiar Mohammadi | |
Scientific Director of the Competence Cluster | |
Universität zu Lübeck | |
Ratzeburger Allee 160 | |
23562 Lübeck | |
Mail: | esfandiar.mohammadi(at)uni-luebeck.de |
Tel.: | +49 451 3101 6609 |
Fax: | +49 451 3101 6604 |
Prof. Dr. Esfandiar Mohammadi
Universität zu Lübeck
Institut für IT-Sicherheit
Ratzeburger Allee 160
23562 Lübeck
Homepage: https://www.its.uni-luebeck.de
Topic: Computer science
Sub-topic(s): Privacy-Preserving Technologies
Funded by

