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Mario Fritz – CISPA Helmholtz Center for Information Security

Mario Fritz – CISPA Helmholtz Center for Information Security

Prof. Dr. Mario Fritz


Faculty
CISPA Helmholtz Center for Information Security

Professor
Saarland University

Fellow
European Laboratory for Learning and Intelligent Systems (ELLIS)


Google Scholar 

Semantic Scholar


Our group is working on Trustworthy AI and AI Security and Safety in various domains like Cybersecurity, Health, Computer Vision, Natural Language Processing.


We are looking for PhD students and Post-Docs! Please get in touch.
We also offer student projects, bachelor/master thesis, internships.

Recent projects and initiatives related to trustworthy AI/ML, health, privacy:

  • PI: European Large Open Multi-Modal Foundation Models for Robust Generalization on Arbitrary Data Streams (ELLIOT)
  • Coordinator and PI: European Lighthouse on Secure and Safe AI (ELSA)
  • Coordinator and PI: PriSyn: Representative, synthetic health data with strong privacy guarantees (BMBF)
  • PI: AIgency “Opportunities and Risks of generative AI in Cybersecurity” (BMBF)
  • PI: PrivateAIM – sichere verteilte Auswertung medizinischer Daten (Medizin Informatik Initiative)
  • Leading Scientist: Helmholtz Medical Security, Privacy, and AI Research Center (HMSP)
  • Coordinator and PI: PriSyn: Representative, synthetic health data with strong privacy guarantees
  • Coordinator and PI: ImageTox: Automated image-based detection of early toxicity events in zebrafish larvae
  • PI: Integrated Early Warning System for Local Recognition, Prevention, and Control for Epidemic Outbreaks (LOKI)
  • Partner-PI: The German Human Genome-Phenome Archive (GHGA)
  • Coordinator and PI: Trustworthy Federated Data Analytics Project (TFDA)
  • Coordinator and PI: Protecting Genetic Data with Synthetic Cohorts from Deep Generative Models (PRO-GENE-GEN)
  • Member of working group in “Forum Gesundheit” of BMBF: “AG Nutzbarmachung digitaler Daten für KI-Entwicklungen in der Gesundheitsforschung”

Recent activities w.r.t. policy, regulation, outreach

  • Frontier AI expert Findings on EU competitiveness, sovereignty and security
  • Member of the AI Act Scientific Panel
  • Expert for AI Cybersecurity Uplift Study “Toward Quantitative Modeling of Cybersecurity Risks Due to AI Misuse”
  • Independent Expert study on technical means for implementing article 50 of EU AI Act towards the code of practice
  • Scientific Lead of the CISPA-ELLIS Summerschool 2025 on “Trustworthy AI – Secure and Safe Foundation Models”
  • Panel on “Loss of Control” at EU AI Office Workshop on “Towards defining best practices for systemic risk evaluations”
  • Keynote on “Security and Safety of LLMs and AI Agents” at 18th ACM International Conference on Web Search and Data Mining
  • Talk on “Fundamental Risks in the Current Deployment of General-Purpose AI Models: What Have We (Not) Learnt From Cybersecurity?” at European AI Office workshop “Evaluating General-Purpose AI Models with Systemic Risk”
  • Expert opinion for evidence review report “Successful and timely uptake of artificial intelligence in science in the EU”
  • Co-Author “ELSA Strategic Research Agenda: Facing the Grand Challenges of Secure and Safe AI”
  • Co-Author “AI, Data, and Robotics ‘made in Europe’: Research agendas from the EU AI and robotics Networks of Excellence”
  • Lecture at Artificial Intelligence Doctoral Academy (AIDA) on “Trustworthy AI and A Cybersecurity Perspective on Large Language Models”

2011 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Data privacy;Biomedical measurement;Data protection;Technology;Privacy;Law;Identification of persons;Federated learning;Surveys;Protection;Biomedical research;federated learning;federated analytics;privacy;data protection

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2026

Journal Articles

An exploratory survey study toward a conceptual framework for structuring the integration of privacy-enhancing technologies in federated learning and analytics

Hammam Abu Attieh; Mehmed Halilovic; Raouf Kerkouche; Shadi Rahimian; Hui-Po Wang; Raphael Rehms; Georgios Kaissis; Alexander Ziller; Jonas Kuntzer; Karen Otte; Thierry Meurers; Mario Fritz; Daniel Rückert; Fabian Prasser

An exploratory survey study toward a conceptual framework for structuring the integration of privacy-enhancing technologies in federated learning and analytics Journal Article

In: IEEE Access, pp. 1-1, 2026.

Links | BibTeX | Tags: Data privacy;Biomedical measurement;Data protection;Technology;Privacy;Law;Identification of persons;Federated learning;Surveys;Protection;Biomedical research;federated learning;federated analytics;privacy;data protection

@article{11433415,
title = {An exploratory survey study toward a conceptual framework for structuring the integration of privacy-enhancing technologies in federated learning and analytics},
author = {Hammam Abu Attieh and Mehmed Halilovic and Raouf Kerkouche and Shadi Rahimian and Hui-Po Wang and Raphael Rehms and Georgios Kaissis and Alexander Ziller and Jonas Kuntzer and Karen Otte and Thierry Meurers and Mario Fritz and Daniel Rückert and Fabian Prasser},
url = {https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11433415},
doi = {10.1109/ACCESS.2026.3672991},
year = {2026},
date = {2026-01-01},
urldate = {2026-01-01},
journal = {IEEE Access},
pages = {1-1},
keywords = {Data privacy;Biomedical measurement;Data protection;Technology;Privacy;Law;Identification of persons;Federated learning;Surveys;Protection;Biomedical research;federated learning;federated analytics;privacy;data protection},
pubstate = {published},
tppubtype = {article}
}

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  • https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11433415
  • doi:10.1109/ACCESS.2026.3672991

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