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

Fuente: arXiv
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Hauptverfasser: Bachlechner, Daniel, Hetfleisch, Ruben, Krenn, Stephan, Lorünser, Thomas, Rader, Michael
Format: Preprint
Veröffentlicht: 2024
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author Bachlechner, Daniel
Hetfleisch, Ruben
Krenn, Stephan
Lorünser, Thomas
Rader, Michael
author_facet Bachlechner, Daniel
Hetfleisch, Ruben
Krenn, Stephan
Lorünser, Thomas
Rader, Michael
contents 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 technologies available matching their needs. Finally, existing gaps are identified, highlighting research potential to advance the field.
format Preprint
id arxiv_https___arxiv_org_abs_2408_15694
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Protecting Privacy in Federated Time Series Analysis: A Pragmatic Technology Review for Application Developers
Bachlechner, Daniel
Hetfleisch, Ruben
Krenn, Stephan
Lorünser, Thomas
Rader, Michael
Cryptography and Security
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 technologies available matching their needs. Finally, existing gaps are identified, highlighting research potential to advance the field.
title Protecting Privacy in Federated Time Series Analysis: A Pragmatic Technology Review for Application Developers
topic Cryptography and Security
url https://arxiv.org/abs/2408.15694