Protecting Privacy in Federated Time Series Analysis: A Pragmatic Technology Review for Application Developers

Daniel Bachlechner, Ruben Hetfleisch, Stephan Krenn, Thomas Lorünser, Thomas Lorünser, Michael Rader

2025

Abstract

The federated analysis of sensitive time series has huge potential in various domains, such as healthcare or manufacturing. Yet, to fully unlock this potential, requirements imposed by various stakeholders must be fulfilled, regarding, e.g., efficiency or trust assumptions. While many of these requirements can be addressed by deploying advanced secure computation paradigms such as fully homomorphic encryption, certain aspects require an integration with additional privacy-preserving technologies. In this work, we perform a qualitative requirements elicitation based on selected real-world use cases. We match the derived requirements categories against the features and guarantees provided by available technologies. For each technology, we additionally perform a maturity assessment, including the state of standardization and availability on the market. Furthermore, we provide a decision tree supporting application developers in identifying the most promising candidate technologies as a starting point for further investigation. Finally, existing gaps are identified, highlighting research potential to advance the field.

Paper Citation

in Harvard Style

Bachlechner D., Hetfleisch R., Krenn S., Lorünser T. and Rader M. (2025). Protecting Privacy in Federated Time Series Analysis: A Pragmatic Technology Review for Application Developers. In Proceedings of the 15th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER; ISBN 978-989-758-747-4, SciTePress, pages 198-210. DOI: 10.5220/0013356100003950

in Bibtex Style

@conference{closer25,
author={Daniel Bachlechner and Ruben Hetfleisch and Stephan Krenn and Thomas Lorünser and Michael Rader},
title={Protecting Privacy in Federated Time Series Analysis: A Pragmatic Technology Review for Application Developers},
booktitle={Proceedings of the 15th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER},
year={2025},
pages={198-210},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013356100003950},
isbn={978-989-758-747-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER
TI - Protecting Privacy in Federated Time Series Analysis: A Pragmatic Technology Review for Application Developers
SN - 978-989-758-747-4
AU - Bachlechner D.
AU - Hetfleisch R.
AU - Krenn S.
AU - Lorünser T.
AU - Rader M.
PY - 2025
SP - 198
EP - 210
DO - 10.5220/0013356100003950
PB - SciTePress