Demo - MedTech Chain: Decentralised, Secure and Privacy-preserving Platform for Medical Device Data Research∗

Alin Petru-Rosu; Tamara Tataru; Jegor Zelenjak; Roland Kromes; Zekeriya Erkin

doi:10.1109/WIFS61860.2024.10810716

Demo - MedTech Chain: Decentralised, Secure and Privacy-preserving Platform for Medical Device Data Research^∗

Alin Petru-Rosu^*, Tamara Tataru, Jegor Zelenjak, Roland Kromes, Zekeriya Erkin

^*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

Abstract

Employing blockchain and privacy-enhancing technologies, MedTech Chain promises an authenticated, decentralised, secure, and privacy-preserving environment for the real-time research and monitoring of medical device data. Through its querying functionalities, the platform can provide valuable insights for threat intelligence, medical research and hospital management. To our knowledge, the approach is among the first to employ ϵ-differential privacy in the context of medical device data. The current work details the framework’s functionality and demonstrates a negligible time overhead induced by ϵ-differential privacy to data analysis.

Original language	English
Title of host publication	Proceedings - 16th IEEE International Workshop on Information Forensics and Security, WIFS 2024
Publisher	IEEE
Number of pages	3
ISBN (Electronic)	9798350364422
DOIs	https://doi.org/10.1109/WIFS61860.2024.10810716
Publication status	Published - 2024
Event	16th IEEE International Workshop on Information Forensics and Security, WIFS 2024 - Rome, Italy Duration: 2 Dec 2024 → 5 Dec 2024

Publication series

Name	Proceedings - 16th IEEE International Workshop on Information Forensics and Security, WIFS 2024

Conference

Conference	16th IEEE International Workshop on Information Forensics and Security, WIFS 2024
Country/Territory	Italy
City	Rome
Period	2/12/24 → 5/12/24

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

blockchain
healthcare
Hyperledger Fabric
IoT
networked medical devices
privacy
security
ϵ-differential privacy

Access to Document

10.1109/WIFS61860.2024.10810716

Demo_-_MedTech_Chain_Decentralised_Secure_and_Privacy-preserving_Platform_for_Medical_Device_Data_ResearchFinal published version, 419 KB

Cite this

Petru-Rosu, A., Tataru, T., Zelenjak, J., Kromes, R., & Erkin, Z. (2024). Demo - MedTech Chain: Decentralised, Secure and Privacy-preserving Platform for Medical Device Data Research^∗. In Proceedings - 16th IEEE International Workshop on Information Forensics and Security, WIFS 2024 (Proceedings - 16th IEEE International Workshop on Information Forensics and Security, WIFS 2024). IEEE. https://doi.org/10.1109/WIFS61860.2024.10810716

Petru-Rosu, Alin ; Tataru, Tamara ; Zelenjak, Jegor et al. / Demo - MedTech Chain : Decentralised, Secure and Privacy-preserving Platform for Medical Device Data Research^∗. Proceedings - 16th IEEE International Workshop on Information Forensics and Security, WIFS 2024. IEEE, 2024. (Proceedings - 16th IEEE International Workshop on Information Forensics and Security, WIFS 2024).

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abstract = "Employing blockchain and privacy-enhancing technologies, MedTech Chain promises an authenticated, decentralised, secure, and privacy-preserving environment for the real-time research and monitoring of medical device data. Through its querying functionalities, the platform can provide valuable insights for threat intelligence, medical research and hospital management. To our knowledge, the approach is among the first to employ ϵ-differential privacy in the context of medical device data. The current work details the framework{\textquoteright}s functionality and demonstrates a negligible time overhead induced by ϵ-differential privacy to data analysis.",

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author = "Alin Petru-Rosu and Tamara Tataru and Jegor Zelenjak and Roland Kromes and Zekeriya Erkin",

note = "Green Open Access added to TU Delft Institutional Repository {\textquoteleft}You share, we take care!{\textquoteright} – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. ; 16th IEEE International Workshop on Information Forensics and Security, WIFS 2024 ; Conference date: 02-12-2024 Through 05-12-2024",

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language = "English",

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Petru-Rosu, A, Tataru, T, Zelenjak, J, Kromes, R & Erkin, Z 2024, Demo - MedTech Chain: Decentralised, Secure and Privacy-preserving Platform for Medical Device Data Research^∗. in Proceedings - 16th IEEE International Workshop on Information Forensics and Security, WIFS 2024. Proceedings - 16th IEEE International Workshop on Information Forensics and Security, WIFS 2024, IEEE, 16th IEEE International Workshop on Information Forensics and Security, WIFS 2024, Rome, Italy, 2/12/24. https://doi.org/10.1109/WIFS61860.2024.10810716

Demo - MedTech Chain: Decentralised, Secure and Privacy-preserving Platform for Medical Device Data Research^∗. / Petru-Rosu, Alin; Tataru, Tamara; Zelenjak, Jegor et al.
Proceedings - 16th IEEE International Workshop on Information Forensics and Security, WIFS 2024. IEEE, 2024. (Proceedings - 16th IEEE International Workshop on Information Forensics and Security, WIFS 2024).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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AU - Zelenjak, Jegor

AU - Kromes, Roland

AU - Erkin, Zekeriya

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Petru-Rosu A, Tataru T, Zelenjak J, Kromes R , Erkin Z. Demo - MedTech Chain: Decentralised, Secure and Privacy-preserving Platform for Medical Device Data Research^∗. In Proceedings - 16th IEEE International Workshop on Information Forensics and Security, WIFS 2024. IEEE. 2024. (Proceedings - 16th IEEE International Workshop on Information Forensics and Security, WIFS 2024). doi: 10.1109/WIFS61860.2024.10810716