Privacy preserving federated machine learning and blockchaining for reduced cyber risks in a world of distributed healthcare

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Mechanisms for removing sensitive information from the blockchain

Set of (novel) attack vectors and countermeasures

Set of novel attack vectors and countermeasures

Explanation strategies, i.e. post-hoc vs. ante-hoc approaches

Explanation strategies, i.e., post-hoc vs. ante-hoc approaches

End-user centred explanatory interfaces for the human-in-the-loop
Manuscript on Usability process
"Report on implementation of assessment, requirement criteria, and ""stress testing"""

Report on implementation of assessment, requirement criteria, and “stress testing”

Framework for Local Sphere privacy-aware federated learning on graphs
Global discovery mechanism based on blockchains
KPIs and metrics for local execution platforms
Working PAML-Layer with low distortion

Working PAMLLayer with low distortion

Gender action report

Gender action plan

Manuscript on Risk management process
Experimental results for shape and composition of connection surfaces
Model for defining user rights in federated machine learning
Secure Architecture and safety evaluation
Manuscript on Quality management process
Risk assessment methodology
Test report on different graph types
Local blockchain mechanism
Test report on different classifier ensembles
Manuscript on Lifecycle process
Selected smart contract mechanism featuring user rights management
Integrated evaluation results for classifier ensembles in a federated approach
Feedback on public data performance
Survey on graph parallelism
Prototypical implementation of phase 3 and evaluation results
Report on performance benchmarks

Prototypical implementation of phase 2 and evaluation results
App store ready and extendible by developers
User interfaces usable for patients, project managers, and developers
Federated machine learning apps running in app store
Federated multi-OMICS system-medicine based clustering software available for download
Entire Federated Clustering pipeline software available for download
Project manager and patients can control access rights with integrated blockchain
Implementation and Integration of Layman-friendly interfaces

Project leaflet for clinical staff
Go-online of the public project website
Video explaining the FeatureCloud Platform
Project leaflet for patients

Integration of the blockchain-based user and data rights management and production ready software available for download
Evaluation of federated vs. non-federated machine learning

Pubblicazioni

Flimma: a federated and privacy-preserving tool for differential gene expression analysis

Autori: Olga Zolotareva, Reza Nasirigerdeh, Julian Matschinske, Reihaneh Torkzadehmahani, Mohammad Bakhtiari, Tobias Frisch, Julian Späth, David B. Blumenthal, Amir Abbasinejad, Paolo Tieri, Georgios Kaissis, Daniel Rückert, Nina K. Wenke, Markus List, and Jan Baumbach
Pubblicato in: Genome Biology, Numero 22, 2021, ISSN 1474-760X
Editore: Springer Nature
DOI: 10.1186/s13059-021-02553-2

GNN-SubNet: disease subnetwork detection with explainable Graph Neural Networks

Autori: Bastian Pfeifer, Afan Secic, Anna Saranti, and Andreas Holzinger
Pubblicato in: Bioinformatics, Numero 38 (2), 2022, Pagina/e ii120–ii126, ISSN 1367-4811
Editore: Oxford University Press
DOI: 10.1093/bioinformatics/btac478

Privacy-aware multi-institutional time-to-event studies

Autori: Julian Späth, Julian Matschinske, Frederick K. Kamanu, Sabina A. Murphy, Olga Zolotareva, Mohammad Bakhtiari, Elliott M. Antman, Joseph Loscalzo, Alissa Brauneck, Louisa Schmalhorst, Gabriele Buchholtz, Jan Baumbach
Pubblicato in: PLOS Digital Health, 2022, ISSN 2767-3170
Editore: PLOS
DOI: 10.1371/journal.pdig.0000101

Verifying compliance in process choreographies: Foundations, algorithms, and implementation

Autori: Walid Fdhila, David Knuplesch, Stefanie Rinderle-Ma, and Manfred Reichert
Pubblicato in: Information Systems, Numero 108, 2022, ISSN 0306-4379
Editore: Elsevier Science & Technology
DOI: 10.1016/j.is.2022.101983

I Know What You Trained Last Summer: A Survey on Stealing Machine Learning Models and Defences

Autori: Daryna Oliynyk, Rudolf Mayer, Andreas Rauber
Pubblicato in: ACM Computing Surveys, Numero 55 (14s), 2023, Pagina/e Article No: 324, ISSN 1557-7341
Editore: Association for Computing Machinery
DOI: 10.1145/3595292

Privacy-Preserving Artificial Intelligence Techniques in Biomedicine

Autori: Reihaneh Torkzadehmahani, Reza Nasirigerdeh, David B. Blumenthal, Tim Kacprowski, Markus List, Julian Matschinske, Julian Spaeth, Nina Kerstin Wenke, and Jan Baumbach
Pubblicato in: Methods Inf Med, Numero 61, 2022, Pagina/e e12-e27, ISSN 0026-1270
Editore: Schattauer
DOI: 10.1055/s-0041-1740630

Multi-omics disease module detection with an explainable Greedy Decision Forest

Autori: Pfeifer, B., Baniecki, H., Saranti, A. et al. . Sci Rep 12, 16857
Pubblicato in: Scientific Reports (Nature), Numero 12, 2022, Pagina/e Article number: 16857, ISSN 2045-2322
Editore: Nature Publishing Group
DOI: 10.1038/s41598-022-21417-8

sPLINK: a hybrid federated tool as a robust alternative to meta-analysis in genome-wide association studies

Autori: Reza Nasirigerdeh, Reihaneh Torkzadehmahani, Julian Matschinske, Tobias Frisch, Markus List, Julian Späth, Stefan Weiss, Uwe Völker, Esa Pitkänen, Dominik Heider, Nina Kerstin Wenke, Georgios Kaissis, Daniel Rueckert, Tim Kacprowski, and Jan Baumbach
Pubblicato in: Genome Biology, Numero 23, 2022, ISSN 1474-760X
Editore: Springer Nature
DOI: 10.1186/s13059-021-02562-1

Molecular networks in Network Medicine: Development and applications.

Autori: Edwin K. Silverman; Harald H.H.W. Schmidt; Eleni Anastasiadou; Lucia Altucci; Marco Angelini; Lina Badimon; Jean-Luc Balligand; Giuditta Benincasa; Giovambattista Capasso; Federica Conte; Antonella Di Costanzo; Lorenzo Farina; Giulia Fiscon; Laurent Gatto; Michele Gentili; Joseph Loscalzo; Cinzia Marchese; Claudio Napoli; Paola Paci; Manuela Petti; John Quackenbush; John Quackenbush; Paolo Tieri;
Pubblicato in: Wiley Interdisciplinary Reviews: Systems Biology and Medicine, Numero 12, 2020, Pagina/e e1489, ISSN 1939-5094
Editore: John Wiley and Sons Inc.
DOI: 10.1002/wsbm.1489

Federated horizontally partitioned principal component analysis for biomedical applications

Autori: Anne Hartebrodt and Richard Roettger
Pubblicato in: Bioinformatics Advances, Numero 2, 2022, ISSN 2635-0041
Editore: Oxford University Press
DOI: 10.1093/bioadv/vbac026

CTCFL regulates the PI3K-Akt pathway and it is a target for personalized ovarian cancer therapy

Autori: Marisol Salgado-Albarrán, Julian Späth, Rodrigo González-Barrios, Jan Baumbach, and Ernesto Soto-Reyes
Pubblicato in: Systems Biology and Applications, Numero 8, 2022, ISSN 2056-7189
Editore: Nature Publishing Group
DOI: 10.1038/s41540-022-00214-z

Federated singular value decomposition for high-dimensional data

Autori: Anne Hartebrodt, Richard Röttger, and David Blumenthal
Pubblicato in: Data Mining and Knowledge Discovery, 2023, ISSN 1384-5810
Editore: Kluwer Academic Publishers
DOI: 10.1007/s10618-023-00983-z

Personas for Artificial Intelligence (AI) an Open Source Toolbox

Autori: Andreas Holzinger, Michaela Kargl, Bettina Kipperer, Peter Regitnig, Markus Plass and Heimo Müller
Pubblicato in: IEEE Access, Numero 10, 2022, ISSN 2169-3536
Editore: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/access.2022.3154776

Federated machine learning for a facilitated implementation of Artificial Intelligence in healthcare – a proof of concept study for the prediction of coronary artery calcification scores

Autori: Justus Wolff, Julian Matschinske, Dietrich Baumgart, Anne Pytlik, Andreas Keck, Arunakiry Natarajan, Claudio E. von Schacky, Josch K. Pauling and Jan Baumbach
Pubblicato in: Journal of Integrative Bioinformatics 2022; 19(4):, Numero 19 (4), 2022, Pagina/e 20220032, ISSN 1613-4516
Editore: Informationsmanagement in der Biotechnologie e.V. (IMBio e.V.)
DOI: 10.1515/jib-2022-0032

Federated Random Forests can improve local performance of predictive models for various healthcare applications

Autori: Anne-Christin Hauschild, Marta Lemanczyk, Julian Matschinske, Tobias Frisch, Olga Zolotareva, Andreas Holzinger, Jan Baumbach, and Dominik Heider
Pubblicato in: Bioinformatics, Numero 38, 2022, ISSN 1367-4803
Editore: Oxford University Press
DOI: 10.1093/bioinformatics/btac065

Integrative Analysis of Next-Generation Sequencing for Next-Generation Cancer Research toward Artificial Intelligence

Autori: Youngjun Park, Dominik Heider and Anne-Christin Hauschild
Pubblicato in: Cancers, Numero 13, 2021, ISSN 2072-6694
Editore: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/cancers13133148

Causability and explainability of artificial intelligence in medicine

Autori: Andreas Holzinger, Georg Langs, Helmut Denk, Kurt Zatloukal, Heimo Müller
Pubblicato in: WIREs Data Mining and Knowledge Discovery, Numero 9/4, 2019, ISSN 1942-4787
Editore: John Wiley and Sons Inc.
DOI: 10.1002/widm.1312

On generating trustworthy counterfactual explanations

Autori: Javier Del Ser, Alejandro Barredo-Arrieta, Natalia Díaz-Rodríguez, Francisco Herrera, Anna Saranti, and Andreas Holzinger
Pubblicato in: Information Sciences, Numero 655, 2024, Pagina/e Article Number: 119898, ISSN 0020-0255
Editore: Elsevier BV
DOI: 10.1016/j.ins.2023.119898

Understanding and Explaining Diagnostic Paths: Toward Augmented Decision Making

Autori: Markus Plass; Michaela Kargl; Patrick Nitsche; Emilian Jungwirth; Andreas Holzinger; Heimo Muller
Pubblicato in: IEEE Computer Graphics and Applications, Numero 42 (6), 2022, Pagina/e 47-57, ISSN 0272-1716
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/mcg.2022.3197957

Transfer learning compensates limited data, batch effects and technological heterogeneity in single-cell sequencing

Autori: Youngjun Park, Anne-Christin Hauschild, and Dominik Heider
Pubblicato in: NAR Genomics and Bioinformatics, Numero 3, 2021, ISSN 2631-9268
Editore: Oxford University Press
DOI: 10.1093/nargab/lqab104

Hierarchical association of COPD to principal genetic components of biological systems

Autori: Daniel E. Carlin; Simon J. Larsen; Vikram Sirupurapu; Michael H. Cho; Edwin K. Silverman; Jan Baumbach; Trey Ideker
Pubblicato in: PLoS ONE, Numero 18 (5), 2023, Pagina/e e0286064, ISSN 1932-6203
Editore: Public Library of Science
DOI: 10.1371/journal.pone.0286064

dsMTL: a computational framework for privacy-preserving, distributed multi-task machine learning

Autori: Han Cao, Youcheng Zhang, Jan Baumbach, Paul R Burton, Dominic Dwyer, Nikolaos Koutsouleris, Julian Matschinske, Yannick Marcon, Sivanesan Rajan, Thilo Rieg, Patricia Ryser-Welch, Julian Späth, The COMMITMENT Consortium, Carl Herrmann, Emanuel Schwarz
Pubblicato in: Bioinformatics, Numero 38 (21), 2022, Pagina/e 4919–4926, ISSN 1367-4811
Editore: Oxford University Press
DOI: 10.1093/bioinformatics/btac616

Towards multi-modal causability with Graph Neural Networks enabling information fusion for explainable AI

Autori: Andreas Holzinger, Bernd Malle, Anna Saranti, Bastian Pfeifer
Pubblicato in: Information Fusion, Numero 71, 2021, Pagina/e 28-37, ISSN 1566-2535
Editore: Elsevier BV
DOI: 10.1016/j.inffus.2021.01.008

Privacy of Federated QR Decomposition Using Additive Secure Multiparty Computation

Autori: Hartebrodt A. and Röttger R.
Pubblicato in: IEEE Transactions on Information Forensics and Security, Numero 18, 2023, Pagina/e 5122-5132, ISSN 1556-6013
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tifs.2023.3301710

Robust disease module mining via enumeration of diverse prize-collecting Steiner trees

Autori: Judith Bernett, Dominik Krupke, Sepideh Sadegh, Jan Baumbach, Sándor P Fekete, Tim Kacprowski, Markus List, and David B Blumenthal
Pubblicato in: Bioinformatics, Numero 38, 2022, ISSN 1367-4803
Editore: Oxford University Press
DOI: 10.1093/bioinformatics/btab876

Ensemble-GNN: federated ensemble learning with graph neural networks for disease module discovery and classification

Autori: Bastian Pfeifer; Hryhorii Chereda; Roman Martin; Anna Saranti; Sandra Clemens; Anne-Christin Hauschild; Tim Beißbarth; Andreas Holzinger; Dominik Heider
Pubblicato in: Bioinformatics, Numero 39 (11), 2023, Pagina/e Article ID: btad703, ISSN 1367-4811
Editore: Oxford University Press
DOI: 10.1101/2023.03.22.533772

Federated machine learning in data-protection-compliant research

Autori: Alissa Brauneck, Louisa Schmalhorst, Mohammad Mahdi Kazemi Majdabadi, Mohammad Bakhtiari, Uwe Völker, Christina Caroline Saak, Jan Baumbach, Linda Baumbach & Gabriele Buchholtz
Pubblicato in: Nature Machine Intelligence, Numero 5, 2023, Pagina/e 2–4, ISSN 2522-5839
Editore: Springer Nature Limited
DOI: 10.1038/s42256-022-00601-5

Identifying Appropriate Intellectual Property Protection Mechanisms for Machine Learning Models: A Systematization of Watermarking, Fingerprinting, Model Access, and Attacks

Autori: Isabell Lederer; Rudolf Mayer; Andreas Rauber
Pubblicato in: IEEE Transactions on Neural Networks and Learning Systems, Numero 02 June 2023, 2023, Pagina/e 1-19, ISSN 2162-2388
Editore: IEEE
DOI: 10.1109/tnnls.2023.3270135

Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research

Autori: Franziska Hufsky, Kevin Lamkiewicz, Alexandre Almeida, Abdel Aouacheria, Cecilia Arighi, Alex Bateman, Jan Baumbach, Niko Beerenwinkel, Christian Brandt, Marco Cacciabue, Sara Chuguransky, Oliver Drechsel, Robert D. Finn, Adrian Fritz, Stephan Fuchs, Georges Hattab, Anne-Christin Hauschild, Dominik Heider, Marie Hoffmann, Martin Hölzer, Stefan Hoops, Lars Kaderali, Ioanna Kalvari, Max von Kleist,
Pubblicato in: Briefings in Bioinformatics, Numero 22, 2021, Pagina/e 642–663, ISSN 1477-4054
Editore: Oxford University Press
DOI: 10.1093/bib/bbaa232

On the limits of active module identification

Autori: Olga Lazareva, Jan Baumbach, Markus List, David B Blumenthal
Pubblicato in: Briefings in Bioinformatics, 2021, ISSN 1467-5463
Editore: Oxford University Press
DOI: 10.1093/bib/bbab066

Explainable AI and Multi-Modal Causability in Medicine

Autori: Andreas Holzinger
Pubblicato in: i-com, Numero 19, 2020, Pagina/e 171–179, ISSN 1618-162X
Editore: Oldenbourg Wissenschaftsverlag
DOI: 10.1515/icom-2020-0024

The AIMe registry for artificial intelligence in biomedical research

Autori: Julian Matschinske, Nicolas Alcaraz, Arriel Benis, Martin Golebiewski, Dominik G. Grimm, Lukas Heumos, Tim Kacprowski, Olga Lazareva, Markus List, Zakaria Louadi, Josch K. Pauling, Nico Pfeifer, Richard Röttger, Veit Schwämmle, Gregor Sturm, Alberto Traverso, Kristel Van Steen, Martiela Vaz de Freitas, Gerda Cristal Villalba Silva, Leonard Wee, Nina K. Wenke, Massimiliano Zanin, Olga Zolotareva,
Pubblicato in: Nature Methods, Numero 18, 2021, Pagina/e 1128–1131, ISSN 1548-7091
Editore: Nature Publishing Group
DOI: 10.1038/s41592-021-01241-0

The FeatureCloud Platform for Federated Learning in Biomedicine: A Unified Approach

Autori: Julian Matschinske; Julian Späth; Mohammad Bakhtiari; Niklas Probul; Mohammad Mahdi Kazemi Majdabadi; Reza Nasirigerdeh; Reihaneh Torkzadehmahani; Anne Hartebrodt; Balazs-Attila Orban; Sándor-József Fejér; Olga Zolotareva; Supratim Das; Linda Baumbach; Josch K Pauling; Olivera Tomašević; Béla Bihari; Marcus Bloice; Nina C Donner; Walid Fdhila; Tobias Frisch; Anne-Christin Hauschild; Dominik
Pubblicato in: Journal of Medical Internet Research, Numero 25, 2023, Pagina/e e42621, ISSN 1438-8871
Editore: Journal of medical Internet Research
DOI: 10.2196/42621

Federated Machine Learning, Privacy-Enhancing Technologies, and Data Protection Laws in Medical Research: Scoping Review

Autori: Alissa Brauneck; Louisa Schmalhorst; Mohammad Mahdi Kazemi Majdabadi; Mohammad Bakhtiari; Uwe Völker; Jan Baumbach; Linda Baumbach; Gabriele Buchholtz
Pubblicato in: Journal of Medical Internet Research, Numero 25, 2023, Pagina/e e41588, ISSN 1438-8871
Editore: Journal of medical Internet Research
DOI: 10.2196/41588

The underuse of AI in the health sector: Opportunity costs, success stories, risks and recommendations

Autori: Ugo Pagallo; Shane O’Sullivan; Nathalie Nevejans; Andreas Holzinger; Michael Friebe; Fleur Jeanquartier; Claire Jean-Quartier; Arkadiusz Miernik
Pubblicato in: Health and Technology, Numero 14, 2023, Pagina/e 1-14, ISSN 2190-7188
Editore: Springer Verlag
DOI: 10.1007/s12553-023-00806-7

Exploring the SARS-CoV-2 virus-host-drug interactome for drug repurposing

Autori: Sepideh Sadegh, Julian Matschinske, David B. Blumenthal, Gihanna Galindez, Tim Kacprowski, Markus List, Reza Nasirigerdeh, Mhaned Oubounyt, Andreas Pichlmair, Tim Daniel Rose, Marisol Salgado-Albarrán, Julian Späth, Alexey Stukalov, Nina K. Wenke, Kevin Yuan, Josch K. Pauling, Jan Baumbach
Pubblicato in: Nature Communications, Numero 11/1, 2020, ISSN 2041-1723
Editore: Nature Publishing Group
DOI: 10.1038/s41467-020-17189-2

Fostering reproducibility, reusability, and technology transfer in health informatics

Autori: Anne-Christin Hauschild, Lisa Eick, Joachim Wienbeck, Dominik Heider
Pubblicato in: iScience, Numero 24/7, 2021, Pagina/e 102803, ISSN 2589-0042
Editore: Cell Press journal
DOI: 10.1016/j.isci.2021.102803

Lessons from the COVID-19 pandemic for advancing computational drug repurposing strategies

Autori: Gihanna Galindez, Julian Matschinske, Tim Daniel Rose, Sepideh Sadegh, Marisol Salgado-Albarrán, Julian Späth, Jan Baumbach, Josch Konstantin Pauling
Pubblicato in: Nature Computational Science, Numero 1/1, 2021, Pagina/e 33-41, ISSN 2662-8457
Editore: Nature Publishing Group
DOI: 10.1038/s43588-020-00007-6

Explainability and causability in digital pathology

Autori: Plass, Markus; Kargl, Michaela; Kiehl, Tim‐Rasmus; Regitnig, Peter; Geißler, Christian; Evans, Theodore; Zerbe, Norman; Carvalho, Rita; Holzinger, Andreas; Müller, Heimo
Pubblicato in: The Journal of Pathology: Clinical Research, Numero 9, 2023, Pagina/e 251–260, ISSN 2056-4538
Editore: The Pathological Society of Great Britain and Ireland and John Wiley & Sons Ltd.
DOI: 10.1002/cjp2.322

Toward human-level concept learning: Pattern benchmarking for AI algorithms

Autori: Andreas Holzinger, Anna Saranti, Alessa Angerschmid, Bettina Finzel, Ute Schmid, Heimo Mueller
Pubblicato in: Patterns, Numero 4 (8), 2023, Pagina/e 100788, ISSN 2666-3899
Editore: Cell Press, New York, NY, USA
DOI: 10.1016/j.patter.2023.100788

Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence

Autori: Andreas Holzinger, Matthias Dehmer, Frank Emmert-Streib, Rita Cucchiara, Isabelle Augenstein, Javier Del Ser, Wojciech Samek, Igor Jurisica, and Natali Díaz-Rodríguez
Pubblicato in: Information Fusion, Numero 79, 2022, ISSN 1566-2535
Editore: Elsevier BV
DOI: 10.1016/j.inffus.2021.10.007

Enabling single-cell trajectory network enrichment

Autori: Alexander G. B. Grønning, Mhaned Oubounyt, Kristiyan Kanev, Jesper Lund, Tim Kacprowski, Dietmar Zehn, Richard Röttger, Jan Baumbach
Pubblicato in: Nature Computational Science, Numero 1/2, 2021, Pagina/e 153-163, ISSN 2662-8457
Editore: Nature Publishing Group
DOI: 10.1038/s43588-021-00025-y

Toward Human–AI Interfaces to Support Explainability and Causability in Medical AI

Autori: Andreas Holzinger; Heimo Müller
Pubblicato in: Computer, Numero 25, 2021, ISSN 0018-9162
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/mc.2021.3092610

Achieving Privacy and Tracing Unauthorised Usage: Anonymisation-based Fingerprinting of Private Data

Autori: Tanja Šarčević, Rudolf Mayer, Philipp Adler
Pubblicato in: 2023 IEEE International Conference on Big Data, Numero 18.12.2023, 2023, Pagina/e 5578-5587, ISBN 979-8-3503-2445-7
Editore: IEEE
DOI: 10.1109/bigdata59044.2023.10386209

Analysing Utility Loss in Federated Learning with Differential Privacy

Autori: Anastasia Pustozerova, Jan Baumbach, Rudolf Mayer
Pubblicato in: International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), Numero 3.11.2023, 2023
Editore: IEEE
DOI: 10.13140/rg.2.2.34594.03521

How much is the fork? Fast Probability and Profitability Calculation during Temporary Forks

Autori: Aljosha Judmayer, Nicholas Stifter, Philipp Schindler, and Edgar Weippl
Pubblicato in: Companion Proceedings of the Web Conference 2022, Numero 25 - 29 April 2022, 2022, Pagina/e 1-13, ISBN 978-1-4503-9130-6
Editore: International Association for Cryptologic Research
DOI: 10.1145/3487553.3524627

Human-in-the-Loop Integration with Domain-Knowledge Graphs for Explainable Federated Deep Learning.

Autori: Holzinger A. et al.
Pubblicato in: Holzinger, A., Kieseberg, P., Cabitza, F., Campagner, A., Tjoa, A.M., Weippl, E. (eds) Machine Learning and Knowledge Extraction. CD-MAKE 2023. Lecture Notes in Computer Science, Numero 14065, 2023, ISBN 978-3-031-40836-6
Editore: Springer
DOI: 10.1007/978-3-031-40837-3_4

k-Anonymity on Metagenomic Features in Microbiome Databases

Autori: Rudolf Mayer; Alicja Karlowicz; Markus Hittmeir
Pubblicato in: ARES '23: Proceedings of the 18th International Conference on Availability, Reliability and Security, Numero 18, 2023, Pagina/e 1-11, ISBN 979-8-4007-0772-8
Editore: Association for Computing Machinery, New York, NY, United States
DOI: 10.1145/3600160.3600178

SoK: How private is Bitcoin? Classification and Evaluation of Bitcoin Privacy Techniques

Autori: Simin Ghesmati; Walid Fdhila; Edgar Weippl
Pubblicato in: ARES '22: Proceedings of the 17th International Conference on Availability, Reliability and Security, Numero 17, 2022, Pagina/e 1-14, ISBN 978-1-4503-9670-7
Editore: ACM Digital Library, New York, NY, United States
DOI: 10.1145/3538969.3538971

Potential Applications of Transfer Learning in Limited Biomedical Data

Autori: Park, Y; Hauschild, AC; Heider, D
Pubblicato in: 67. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS), 13. Jahreskongress der Technologie- und Methodenplattform für die vernetzte medizinische Forschung e.V. (TMF); 20220821-20220825; sine loco [digital]; DOCAbstr. 75 /20220819/, Numero 67, 2022
Editore: Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie
DOI: 10.3205/22gmds112

Differentially Private Federated Learning: Privacy and Utility Analysis of Output Perturbation and DP-SGD

Autori: Anastasia Pustozerova; Jan Baumbach; Rudolf Mayer
Pubblicato in: 2023 IEEE International Conference on Big Data (BigData), Numero 18.12.2023, 2023, Pagina/e 5549-5558, ISBN 979-8-3503-2445-7
Editore: IEEE
DOI: 10.1109/bigdata59044.2023.10386466

Usability of Cryptocurrency Wallets Providing CoinJoin Transactions

Autori: Simin Ghesmati, Walid Fdhila and Edgar Weippl
Pubblicato in: Proceedings of the Usable Security and Privacy (USEC) Symposium 2022, 2022, ISBN 1-891562-79-7
Editore: The Internet Society
DOI: 10.14722/usec.2022.23037

A Comparison of Federated Aggregation Strategies and Architectures for Next-word Prediction

Autori: Yana Sakhnovych; Richard Röttger; Rudolf Mayer;
Pubblicato in: 2023 IEEE International Conference on Big Data (BigData), Numero 18.12.2023, 2023, Pagina/e 5569-5577, ISBN 979-8-3503-2445-7
Editore: IEEE
DOI: 10.1109/bigdata59044.2023.10386579

Information Leaks in Federated Learning

Autori: Anastassiya Pustozerova, Rudolf Mayer
Pubblicato in: Proceedings 2020 Workshop on Decentralized IoT Systems and Security, 2020, ISBN 1-891562-64-9
Editore: Internet Society
DOI: 10.14722/diss.2020.23004

Data Poisoning in Sequential and Parallel Federated Learning

Autori: Florian Nuding and Rudolf Mayer
Pubblicato in: IWSPA '22: Proceedings of the 2022 ACM on International Workshop on Security and Privacy Analytics, 2022, Pagina/e 24-34, ISBN 978-1-4503-9230-3
Editore: Association for Computing Machinery (ACM)
DOI: 10.1145/3510548.3519372

The Tower of Babel in Explainable Artificial Intelligence (XAI)

Autori: David Schneeberger, Richard Röttger, Federico Cabitza, Andrea Campagner, Markus Plass, Heimo Müller & Andreas Holzinger
Pubblicato in: Holzinger, A., Kieseberg, P., Cabitza, F., Campagner, A., Tjoa, A.M., Weippl, E. (eds) Machine Learning and Knowledge Extraction. CD-MAKE 2023. Lecture Notes in Computer Science, Numero 14065, 2023, Pagina/e 65–81, ISBN 978-3-031-40836-6
Editore: Springer
DOI: 10.1007/978-3-031-40837-3_5

An Efficient Approach for Anonymising the Structure of Heterogeneous Graphs

Autori: Requena GA, Mayer R, and Ekelhart A
Pubblicato in: 2022 IEEE International Conference on Big Data (Big Data), 2022, Pagina/e 5783-5791, ISBN 978-1-6654-8045-1
Editore: IEEE
DOI: 10.1109/bigdata55660.2022.10020301

Visualization of Histopathological Decision Making Using a Roadbook Metaphor

Autori: Birgit Pohn; Marie-Christina Mayer; Robert Reihs; Andreas Holzinger; Kurt Zatloukal; Heimo Müller
Pubblicato in: 23rd International Conference Information Visualisation (IV), Numero 02-05 July 2019, 2019, Pagina/e 392-397, ISBN 978-1-7281-2838-2
Editore: IEEE
DOI: 10.1109/iv.2019.00073

Adaptive Attacks and Targeted Fingerprinting of Relational Data

Autori: Šarčević T, Mayer R, and Rauber A
Pubblicato in: 2022 IEEE International Conference on Big Data (Big Data), 2022, Pagina/e 5792-5801, ISBN 978-1-6654-8045-1
Editore: IEEE
DOI: 10.1109/bigdata55660.2022.10020266

Poisoning Attacks in Federated Learning - An Evaluation on Traffic Sign Classification

Autori: Florian Nuding, Rudolf Mayer
Pubblicato in: Proceedings of the Tenth ACM Conference on Data and Application Security and Privacy, 2020, Pagina/e 168-170, ISBN 9781450371070
Editore: ACM
DOI: 10.1145/3374664.3379534

Estimating (Miner) Extractable Value is Hard, Let’s Go Shopping!

Autori: Aljosha Judmayer, Nicholas Stifter, Philipp Schindler, and Edgar Weippl
Pubblicato in: Matsuo, S., et al. Financial Cryptography and Data Security (FC 2022). FC 2022 International Workshops. Lecture Notes in Computer Science, Numero Vol. 13412, 2023, ISBN 978-3-031-32414-7
Editore: Springer
DOI: 10.1007/978-3-031-32415-4_6

Opportunistic Algorithmic Double-Spending: How I Learned to Stop Worrying and Love the Fork

Autori: Stifter N, Judmayer A, Schindler P, and Weippl E
Pubblicato in: Atluri, V., Di Pietro, R., Jensen, C.D., Meng, W. (eds) Computer Security – ESORICS 2022. Lecture Notes in Computer Science, Numero 13554, 2022, ISBN 978-3-031-17139-0
Editore: Springer
DOI: 10.1007/978-3-031-17140-6_3

Towards a Deeper Understanding of How a Pathologist Makes a Diagnosis: Visualization of the Diagnostic Process in Histopathology

Autori: Birgit Pohn; Michaela Kargl; Robert Reihs; Andreas Holzinger; Kurt Zatloukal; Heimo Müller
Pubblicato in: 2019 IEEE Symposium on Computers and Communications (ISCC), Numero 29 June - 03 July 2019, 2019, Pagina/e 1081-1086, ISBN 978-1-7281-2999-0
Editore: IEEE
DOI: 10.1109/iscc47284.2019.8969598

Federated Principal Component Analysis for Genome-Wide Association Studies

Autori: Anne Hartebrodt, Reza Nasirigerdeh, David Blumenthal, and Richard Röttger
Pubblicato in: IEEE International Conference on Data Mining (ICDM) 2021, 2021, Pagina/e 1090-1095, ISBN 978-1-6654-2398-4
Editore: IEEE
DOI: 10.1109/icdm51629.2021.00127

Challenges and Opportunities of Blockchain for Auditable Processes in the Healthcare Sector

Autori: Fdhila W, Stifter N, and Judmayer A
Pubblicato in: Marrella, A., et al. Business Process Management: Blockchain, Robotic Process Automation, and Central and Eastern Europe Forum. BPM 2022. Lecture Notes in Business Information Processing, Numero 459, 2022, ISBN 978-3-031-16167-4
Editore: Springer
DOI: 10.1007/978-3-031-16168-1_5

User-Perceived Privacy in Blockchain

Autori: Simin Ghesmati, Walid Fdhila, and Edgar Weippl
Pubblicato in: Financial Cryptography and Data Security. FC 2022 International Workshops. Lecture Notes in Computer Science, Numero vol. 13412, 2023, ISBN 978-3-031-32414-7
Editore: Springer
DOI: 10.1007/978-3-031-32415-4_12

Anomaly Detection from Distributed Data Sources via Federated Learning

Autori: Florencia Cavallin and Rudolf Mayer
Pubblicato in: Lecture Notes in Networks and Systems, Numero 450, 2022, ISBN 978-3-030-99586-7
Editore: Springer
DOI: 10.1007/978-3-030-99587-4_27

Training Effective Neural Networks on Structured Data with Federated Learning

Autori: Anastasia Pustozerova, Andreas Rauber, Rudolf Mayer
Pubblicato in: Advanced Information Networking and Applications - Proceedings of the 35th International Conference on Advanced Information Networking and Applications (AINA-2021), Volume 2, Numero 226, 2021, Pagina/e 394-406, ISBN 978-3-030-75074-9
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-75075-6_32

An Analysis of Different Notions of Effectiveness in k-Anonymity

Autori: Tanja Šarčević, David Molnar, Rudolf Mayer
Pubblicato in: Privacy in Statistical Databases - UNESCO Chair in Data Privacy, International Conference, PSD 2020, Tarragona, Spain, September 23–25, 2020, Proceedings, Numero 12276, 2020, Pagina/e 121-135, ISBN 978-3-030-57520-5
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-57521-2_9

Federated Unsupervised Machine Learning

Autori: Hartebrodt, Anne
Pubblicato in: SDU - University of Southern Denmark, Department of Mathematics and Computer Science, Numero n/a, 2021, Pagina/e 1-192
Editore: Syddansk Universitet, Det Naturvidenskabelige Fakultet
DOI: 10.21996/z4yw-jm67

What is Meant by Permissionless Blockchains?

Autori: Nicholas Stifter, Aljosha Judmayer, Philipp Schindler, Andreas Kern, and Walid Fdhila
Pubblicato in: Cryptology ePrint Archive (Preprint), Numero 23, 2021, Pagina/e See video of paper presentation: https://ucloud.univie.ac.at/index.php/s/eWa6ibu4YgFjfFO, ISSN 1432-1378
Editore: The International Association for Cryptologic Research (IACR)'

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