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

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

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

Publicaciones

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

Autores: 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
Publicado en: Genome Biology, Edición 22, 2021, ISSN 1474-760X
Editor: Springer Nature
DOI: 10.1186/s13059-021-02553-2

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

Autores: Bastian Pfeifer, Afan Secic, Anna Saranti, and Andreas Holzinger
Publicado en: Bioinformatics, Edición 38 (2), 2022, Página(s) ii120–ii126, ISSN 1367-4811
Editor: Oxford University Press
DOI: 10.1093/bioinformatics/btac478

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

Autores: 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
Publicado en: PLOS Digital Health, 2022, ISSN 2767-3170
Editor: PLOS
DOI: 10.1371/journal.pdig.0000101

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

Autores: Walid Fdhila, David Knuplesch, Stefanie Rinderle-Ma, and Manfred Reichert
Publicado en: Information Systems, Edición 108, 2022, ISSN 0306-4379
Editor: 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

Autores: Daryna Oliynyk, Rudolf Mayer, Andreas Rauber
Publicado en: ACM Computing Surveys, Edición 55 (14s), 2023, Página(s) Article No: 324, ISSN 1557-7341
Editor: Association for Computing Machinery
DOI: 10.1145/3595292

Privacy-Preserving Artificial Intelligence Techniques in Biomedicine

Autores: Reihaneh Torkzadehmahani, Reza Nasirigerdeh, David B. Blumenthal, Tim Kacprowski, Markus List, Julian Matschinske, Julian Spaeth, Nina Kerstin Wenke, and Jan Baumbach
Publicado en: Methods Inf Med, Edición 61, 2022, Página(s) e12-e27, ISSN 0026-1270
Editor: Schattauer
DOI: 10.1055/s-0041-1740630

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

Autores: Pfeifer, B., Baniecki, H., Saranti, A. et al. . Sci Rep 12, 16857
Publicado en: Scientific Reports (Nature), Edición 12, 2022, Página(s) Article number: 16857, ISSN 2045-2322
Editor: 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

Autores: 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
Publicado en: Genome Biology, Edición 23, 2022, ISSN 1474-760X
Editor: Springer Nature
DOI: 10.1186/s13059-021-02562-1

Molecular networks in Network Medicine: Development and applications.

Autores: 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;
Publicado en: Wiley Interdisciplinary Reviews: Systems Biology and Medicine, Edición 12, 2020, Página(s) e1489, ISSN 1939-5094
Editor: John Wiley and Sons Inc.
DOI: 10.1002/wsbm.1489

Federated horizontally partitioned principal component analysis for biomedical applications

Autores: Anne Hartebrodt and Richard Roettger
Publicado en: Bioinformatics Advances, Edición 2, 2022, ISSN 2635-0041
Editor: Oxford University Press
DOI: 10.1093/bioadv/vbac026

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

Autores: Marisol Salgado-Albarrán, Julian Späth, Rodrigo González-Barrios, Jan Baumbach, and Ernesto Soto-Reyes
Publicado en: Systems Biology and Applications, Edición 8, 2022, ISSN 2056-7189
Editor: Nature Publishing Group
DOI: 10.1038/s41540-022-00214-z

Federated singular value decomposition for high-dimensional data

Autores: Anne Hartebrodt, Richard Röttger, and David Blumenthal
Publicado en: Data Mining and Knowledge Discovery, 2023, ISSN 1384-5810
Editor: Kluwer Academic Publishers
DOI: 10.1007/s10618-023-00983-z

Personas for Artificial Intelligence (AI) an Open Source Toolbox

Autores: Andreas Holzinger, Michaela Kargl, Bettina Kipperer, Peter Regitnig, Markus Plass and Heimo Müller
Publicado en: IEEE Access, Edición 10, 2022, ISSN 2169-3536
Editor: 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

Autores: Justus Wolff, Julian Matschinske, Dietrich Baumgart, Anne Pytlik, Andreas Keck, Arunakiry Natarajan, Claudio E. von Schacky, Josch K. Pauling and Jan Baumbach
Publicado en: Journal of Integrative Bioinformatics 2022; 19(4):, Edición 19 (4), 2022, Página(s) 20220032, ISSN 1613-4516
Editor: 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

Autores: Anne-Christin Hauschild, Marta Lemanczyk, Julian Matschinske, Tobias Frisch, Olga Zolotareva, Andreas Holzinger, Jan Baumbach, and Dominik Heider
Publicado en: Bioinformatics, Edición 38, 2022, ISSN 1367-4803
Editor: Oxford University Press
DOI: 10.1093/bioinformatics/btac065

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

Autores: Youngjun Park, Dominik Heider and Anne-Christin Hauschild
Publicado en: Cancers, Edición 13, 2021, ISSN 2072-6694
Editor: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/cancers13133148

Causability and explainability of artificial intelligence in medicine

Autores: Andreas Holzinger, Georg Langs, Helmut Denk, Kurt Zatloukal, Heimo Müller
Publicado en: WIREs Data Mining and Knowledge Discovery, Edición 9/4, 2019, ISSN 1942-4787
Editor: John Wiley and Sons Inc.
DOI: 10.1002/widm.1312

On generating trustworthy counterfactual explanations

Autores: Javier Del Ser, Alejandro Barredo-Arrieta, Natalia Díaz-Rodríguez, Francisco Herrera, Anna Saranti, and Andreas Holzinger
Publicado en: Information Sciences, Edición 655, 2024, Página(s) Article Number: 119898, ISSN 0020-0255
Editor: Elsevier BV
DOI: 10.1016/j.ins.2023.119898

Understanding and Explaining Diagnostic Paths: Toward Augmented Decision Making

Autores: Markus Plass; Michaela Kargl; Patrick Nitsche; Emilian Jungwirth; Andreas Holzinger; Heimo Muller
Publicado en: IEEE Computer Graphics and Applications, Edición 42 (6), 2022, Página(s) 47-57, ISSN 0272-1716
Editor: 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

Autores: Youngjun Park, Anne-Christin Hauschild, and Dominik Heider
Publicado en: NAR Genomics and Bioinformatics, Edición 3, 2021, ISSN 2631-9268
Editor: Oxford University Press
DOI: 10.1093/nargab/lqab104

Hierarchical association of COPD to principal genetic components of biological systems

Autores: Daniel E. Carlin; Simon J. Larsen; Vikram Sirupurapu; Michael H. Cho; Edwin K. Silverman; Jan Baumbach; Trey Ideker
Publicado en: PLoS ONE, Edición 18 (5), 2023, Página(s) e0286064, ISSN 1932-6203
Editor: Public Library of Science
DOI: 10.1371/journal.pone.0286064

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

Autores: 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
Publicado en: Bioinformatics, Edición 38 (21), 2022, Página(s) 4919–4926, ISSN 1367-4811
Editor: Oxford University Press
DOI: 10.1093/bioinformatics/btac616

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

Autores: Andreas Holzinger, Bernd Malle, Anna Saranti, Bastian Pfeifer
Publicado en: Information Fusion, Edición 71, 2021, Página(s) 28-37, ISSN 1566-2535
Editor: Elsevier BV
DOI: 10.1016/j.inffus.2021.01.008

Privacy of Federated QR Decomposition Using Additive Secure Multiparty Computation

Autores: Hartebrodt A. and Röttger R.
Publicado en: IEEE Transactions on Information Forensics and Security, Edición 18, 2023, Página(s) 5122-5132, ISSN 1556-6013
Editor: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tifs.2023.3301710

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

Autores: Judith Bernett, Dominik Krupke, Sepideh Sadegh, Jan Baumbach, Sándor P Fekete, Tim Kacprowski, Markus List, and David B Blumenthal
Publicado en: Bioinformatics, Edición 38, 2022, ISSN 1367-4803
Editor: Oxford University Press
DOI: 10.1093/bioinformatics/btab876

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

Autores: Bastian Pfeifer; Hryhorii Chereda; Roman Martin; Anna Saranti; Sandra Clemens; Anne-Christin Hauschild; Tim Beißbarth; Andreas Holzinger; Dominik Heider
Publicado en: Bioinformatics, Edición 39 (11), 2023, Página(s) Article ID: btad703, ISSN 1367-4811
Editor: Oxford University Press
DOI: 10.1101/2023.03.22.533772

Federated machine learning in data-protection-compliant research

Autores: Alissa Brauneck, Louisa Schmalhorst, Mohammad Mahdi Kazemi Majdabadi, Mohammad Bakhtiari, Uwe Völker, Christina Caroline Saak, Jan Baumbach, Linda Baumbach & Gabriele Buchholtz
Publicado en: Nature Machine Intelligence, Edición 5, 2023, Página(s) 2–4, ISSN 2522-5839
Editor: 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

Autores: Isabell Lederer; Rudolf Mayer; Andreas Rauber
Publicado en: IEEE Transactions on Neural Networks and Learning Systems, Edición 02 June 2023, 2023, Página(s) 1-19, ISSN 2162-2388
Editor: IEEE
DOI: 10.1109/tnnls.2023.3270135

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

Autores: 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,
Publicado en: Briefings in Bioinformatics, Edición 22, 2021, Página(s) 642–663, ISSN 1477-4054
Editor: Oxford University Press
DOI: 10.1093/bib/bbaa232

On the limits of active module identification

Autores: Olga Lazareva, Jan Baumbach, Markus List, David B Blumenthal
Publicado en: Briefings in Bioinformatics, 2021, ISSN 1467-5463
Editor: Oxford University Press
DOI: 10.1093/bib/bbab066

Explainable AI and Multi-Modal Causability in Medicine

Autores: Andreas Holzinger
Publicado en: i-com, Edición 19, 2020, Página(s) 171–179, ISSN 1618-162X
Editor: Oldenbourg Wissenschaftsverlag
DOI: 10.1515/icom-2020-0024

The AIMe registry for artificial intelligence in biomedical research

Autores: 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,
Publicado en: Nature Methods, Edición 18, 2021, Página(s) 1128–1131, ISSN 1548-7091
Editor: Nature Publishing Group
DOI: 10.1038/s41592-021-01241-0

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

Autores: 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
Publicado en: Journal of Medical Internet Research, Edición 25, 2023, Página(s) e42621, ISSN 1438-8871
Editor: Journal of medical Internet Research
DOI: 10.2196/42621

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

Autores: Alissa Brauneck; Louisa Schmalhorst; Mohammad Mahdi Kazemi Majdabadi; Mohammad Bakhtiari; Uwe Völker; Jan Baumbach; Linda Baumbach; Gabriele Buchholtz
Publicado en: Journal of Medical Internet Research, Edición 25, 2023, Página(s) e41588, ISSN 1438-8871
Editor: Journal of medical Internet Research
DOI: 10.2196/41588

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

Autores: Ugo Pagallo; Shane O’Sullivan; Nathalie Nevejans; Andreas Holzinger; Michael Friebe; Fleur Jeanquartier; Claire Jean-Quartier; Arkadiusz Miernik
Publicado en: Health and Technology, Edición 14, 2023, Página(s) 1-14, ISSN 2190-7188
Editor: Springer Verlag
DOI: 10.1007/s12553-023-00806-7

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

Autores: 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
Publicado en: Nature Communications, Edición 11/1, 2020, ISSN 2041-1723
Editor: Nature Publishing Group
DOI: 10.1038/s41467-020-17189-2

Fostering reproducibility, reusability, and technology transfer in health informatics

Autores: Anne-Christin Hauschild, Lisa Eick, Joachim Wienbeck, Dominik Heider
Publicado en: iScience, Edición 24/7, 2021, Página(s) 102803, ISSN 2589-0042
Editor: Cell Press journal
DOI: 10.1016/j.isci.2021.102803

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

Autores: Gihanna Galindez, Julian Matschinske, Tim Daniel Rose, Sepideh Sadegh, Marisol Salgado-Albarrán, Julian Späth, Jan Baumbach, Josch Konstantin Pauling
Publicado en: Nature Computational Science, Edición 1/1, 2021, Página(s) 33-41, ISSN 2662-8457
Editor: Nature Publishing Group
DOI: 10.1038/s43588-020-00007-6

Explainability and causability in digital pathology

Autores: Plass, Markus; Kargl, Michaela; Kiehl, Tim‐Rasmus; Regitnig, Peter; Geißler, Christian; Evans, Theodore; Zerbe, Norman; Carvalho, Rita; Holzinger, Andreas; Müller, Heimo
Publicado en: The Journal of Pathology: Clinical Research, Edición 9, 2023, Página(s) 251–260, ISSN 2056-4538
Editor: 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

Autores: Andreas Holzinger, Anna Saranti, Alessa Angerschmid, Bettina Finzel, Ute Schmid, Heimo Mueller
Publicado en: Patterns, Edición 4 (8), 2023, Página(s) 100788, ISSN 2666-3899
Editor: 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

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

Enabling single-cell trajectory network enrichment

Autores: Alexander G. B. Grønning, Mhaned Oubounyt, Kristiyan Kanev, Jesper Lund, Tim Kacprowski, Dietmar Zehn, Richard Röttger, Jan Baumbach
Publicado en: Nature Computational Science, Edición 1/2, 2021, Página(s) 153-163, ISSN 2662-8457
Editor: Nature Publishing Group
DOI: 10.1038/s43588-021-00025-y

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

Autores: Andreas Holzinger; Heimo Müller
Publicado en: Computer, Edición 25, 2021, ISSN 0018-9162
Editor: Institute of Electrical and Electronics Engineers
DOI: 10.1109/mc.2021.3092610

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

Autores: Tanja Šarčević, Rudolf Mayer, Philipp Adler
Publicado en: 2023 IEEE International Conference on Big Data, Edición 18.12.2023, 2023, Página(s) 5578-5587, ISBN 979-8-3503-2445-7
Editor: IEEE
DOI: 10.1109/bigdata59044.2023.10386209

Analysing Utility Loss in Federated Learning with Differential Privacy

Autores: Anastasia Pustozerova, Jan Baumbach, Rudolf Mayer
Publicado en: International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), Edición 3.11.2023, 2023
Editor: IEEE
DOI: 10.13140/rg.2.2.34594.03521

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

Autores: Aljosha Judmayer, Nicholas Stifter, Philipp Schindler, and Edgar Weippl
Publicado en: Companion Proceedings of the Web Conference 2022, Edición 25 - 29 April 2022, 2022, Página(s) 1-13, ISBN 978-1-4503-9130-6
Editor: International Association for Cryptologic Research
DOI: 10.1145/3487553.3524627

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

Autores: Holzinger A. et al.
Publicado en: 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, Edición 14065, 2023, ISBN 978-3-031-40836-6
Editor: Springer
DOI: 10.1007/978-3-031-40837-3_4

k-Anonymity on Metagenomic Features in Microbiome Databases

Autores: Rudolf Mayer; Alicja Karlowicz; Markus Hittmeir
Publicado en: ARES '23: Proceedings of the 18th International Conference on Availability, Reliability and Security, Edición 18, 2023, Página(s) 1-11, ISBN 979-8-4007-0772-8
Editor: 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

Autores: Simin Ghesmati; Walid Fdhila; Edgar Weippl
Publicado en: ARES '22: Proceedings of the 17th International Conference on Availability, Reliability and Security, Edición 17, 2022, Página(s) 1-14, ISBN 978-1-4503-9670-7
Editor: ACM Digital Library, New York, NY, United States
DOI: 10.1145/3538969.3538971

Potential Applications of Transfer Learning in Limited Biomedical Data

Autores: Park, Y; Hauschild, AC; Heider, D
Publicado en: 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/, Edición 67, 2022
Editor: 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

Autores: Anastasia Pustozerova; Jan Baumbach; Rudolf Mayer
Publicado en: 2023 IEEE International Conference on Big Data (BigData), Edición 18.12.2023, 2023, Página(s) 5549-5558, ISBN 979-8-3503-2445-7
Editor: IEEE
DOI: 10.1109/bigdata59044.2023.10386466

Usability of Cryptocurrency Wallets Providing CoinJoin Transactions

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

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

Autores: Yana Sakhnovych; Richard Röttger; Rudolf Mayer;
Publicado en: 2023 IEEE International Conference on Big Data (BigData), Edición 18.12.2023, 2023, Página(s) 5569-5577, ISBN 979-8-3503-2445-7
Editor: IEEE
DOI: 10.1109/bigdata59044.2023.10386579

Information Leaks in Federated Learning

Autores: Anastassiya Pustozerova, Rudolf Mayer
Publicado en: Proceedings 2020 Workshop on Decentralized IoT Systems and Security, 2020, ISBN 1-891562-64-9
Editor: Internet Society
DOI: 10.14722/diss.2020.23004

Data Poisoning in Sequential and Parallel Federated Learning

Autores: Florian Nuding and Rudolf Mayer
Publicado en: IWSPA '22: Proceedings of the 2022 ACM on International Workshop on Security and Privacy Analytics, 2022, Página(s) 24-34, ISBN 978-1-4503-9230-3
Editor: Association for Computing Machinery (ACM)
DOI: 10.1145/3510548.3519372

The Tower of Babel in Explainable Artificial Intelligence (XAI)

Autores: David Schneeberger, Richard Röttger, Federico Cabitza, Andrea Campagner, Markus Plass, Heimo Müller & Andreas Holzinger
Publicado en: 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, Edición 14065, 2023, Página(s) 65–81, ISBN 978-3-031-40836-6
Editor: Springer
DOI: 10.1007/978-3-031-40837-3_5

An Efficient Approach for Anonymising the Structure of Heterogeneous Graphs

Autores: Requena GA, Mayer R, and Ekelhart A
Publicado en: 2022 IEEE International Conference on Big Data (Big Data), 2022, Página(s) 5783-5791, ISBN 978-1-6654-8045-1
Editor: IEEE
DOI: 10.1109/bigdata55660.2022.10020301

Visualization of Histopathological Decision Making Using a Roadbook Metaphor

Autores: Birgit Pohn; Marie-Christina Mayer; Robert Reihs; Andreas Holzinger; Kurt Zatloukal; Heimo Müller
Publicado en: 23rd International Conference Information Visualisation (IV), Edición 02-05 July 2019, 2019, Página(s) 392-397, ISBN 978-1-7281-2838-2
Editor: IEEE
DOI: 10.1109/iv.2019.00073

Adaptive Attacks and Targeted Fingerprinting of Relational Data

Autores: Šarčević T, Mayer R, and Rauber A
Publicado en: 2022 IEEE International Conference on Big Data (Big Data), 2022, Página(s) 5792-5801, ISBN 978-1-6654-8045-1
Editor: IEEE
DOI: 10.1109/bigdata55660.2022.10020266

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

Autores: Florian Nuding, Rudolf Mayer
Publicado en: Proceedings of the Tenth ACM Conference on Data and Application Security and Privacy, 2020, Página(s) 168-170, ISBN 9781450371070
Editor: ACM
DOI: 10.1145/3374664.3379534

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

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

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

Autores: Stifter N, Judmayer A, Schindler P, and Weippl E
Publicado en: Atluri, V., Di Pietro, R., Jensen, C.D., Meng, W. (eds) Computer Security – ESORICS 2022. Lecture Notes in Computer Science, Edición 13554, 2022, ISBN 978-3-031-17139-0
Editor: 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

Autores: Birgit Pohn; Michaela Kargl; Robert Reihs; Andreas Holzinger; Kurt Zatloukal; Heimo Müller
Publicado en: 2019 IEEE Symposium on Computers and Communications (ISCC), Edición 29 June - 03 July 2019, 2019, Página(s) 1081-1086, ISBN 978-1-7281-2999-0
Editor: IEEE
DOI: 10.1109/iscc47284.2019.8969598

Federated Principal Component Analysis for Genome-Wide Association Studies

Autores: Anne Hartebrodt, Reza Nasirigerdeh, David Blumenthal, and Richard Röttger
Publicado en: IEEE International Conference on Data Mining (ICDM) 2021, 2021, Página(s) 1090-1095, ISBN 978-1-6654-2398-4
Editor: IEEE
DOI: 10.1109/icdm51629.2021.00127

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

Autores: Fdhila W, Stifter N, and Judmayer A
Publicado en: 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, Edición 459, 2022, ISBN 978-3-031-16167-4
Editor: Springer
DOI: 10.1007/978-3-031-16168-1_5

User-Perceived Privacy in Blockchain

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

Anomaly Detection from Distributed Data Sources via Federated Learning

Autores: Florencia Cavallin and Rudolf Mayer
Publicado en: Lecture Notes in Networks and Systems, Edición 450, 2022, ISBN 978-3-030-99586-7
Editor: Springer
DOI: 10.1007/978-3-030-99587-4_27

Training Effective Neural Networks on Structured Data with Federated Learning

Autores: Anastasia Pustozerova, Andreas Rauber, Rudolf Mayer
Publicado en: Advanced Information Networking and Applications - Proceedings of the 35th International Conference on Advanced Information Networking and Applications (AINA-2021), Volume 2, Edición 226, 2021, Página(s) 394-406, ISBN 978-3-030-75074-9
Editor: Springer International Publishing
DOI: 10.1007/978-3-030-75075-6_32

An Analysis of Different Notions of Effectiveness in k-Anonymity

Autores: Tanja Šarčević, David Molnar, Rudolf Mayer
Publicado en: Privacy in Statistical Databases - UNESCO Chair in Data Privacy, International Conference, PSD 2020, Tarragona, Spain, September 23–25, 2020, Proceedings, Edición 12276, 2020, Página(s) 121-135, ISBN 978-3-030-57520-5
Editor: Springer International Publishing
DOI: 10.1007/978-3-030-57521-2_9

Federated Unsupervised Machine Learning

Autores: Hartebrodt, Anne
Publicado en: SDU - University of Southern Denmark, Department of Mathematics and Computer Science, Edición n/a, 2021, Página(s) 1-192
Editor: Syddansk Universitet, Det Naturvidenskabelige Fakultet
DOI: 10.21996/z4yw-jm67

What is Meant by Permissionless Blockchains?

Autores: Nicholas Stifter, Aljosha Judmayer, Philipp Schindler, Andreas Kern, and Walid Fdhila
Publicado en: Cryptology ePrint Archive (Preprint), Edición 23, 2021, Página(s) See video of paper presentation: https://ucloud.univie.ac.at/index.php/s/eWa6ibu4YgFjfFO, ISSN 1432-1378
Editor: The International Association for Cryptologic Research (IACR)'

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