"Can I trust the data I see?": a physician's concern on medical data in IoT health architectures

Fariha Tasmin Jaigirdar, Carsten Rudolph, Chris Bain

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

With the increasing advancement of Internet of Things (IoT) enabled systems, smart medical devices open numerous opportunities for the healthcare sector. The success of using such devices in the healthcare industry depends strongly on secured and reliable medical data transmission. Physicians diagnose that data and prescribe medicines and/or give guidelines/instructions/treatment plans for the patients. Therefore, a physician is always concerned about the medical data trustworthiness, because if it is not guaranteed, a savior can become an involuntary foe! This paper analyses two different scenarios to understand the real-life consequences in IoT-based healthcare (IoT-Health) application. Appropriate sequence diagrams for both scenarios show data movement as a basis for determining necessary security requirements in each layer of IoT-Health. We analyse the individual entities of the overall system and develop a system-wide view of trust in IoT-Health. The security analysis pinpoints the research gap in end-to-end trust and indicates the necessity to treat the whole IoT-Health system as an integrated entity. This study highlights the importance of integrated cross-layer security solutions that can deal with the heterogeneous security architectures of IoT healthcare system and finally identifies a possible solution for the open question raised in the security analysis with appropriate future research directions.

Original languageEnglish
Title of host publicationACSW'19 - Proceedings of the Australasian Computer Science Week Multiconference
Subtitle of host publicationSydney, NSW, Australia — January 29 - 31, 2019
EditorsYing Wang, Dale Patterson
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Number of pages10
ISBN (Electronic)9781450366038
DOIs
Publication statusPublished - 2019
EventAustralasian Workshop on Health Informatics and Knowledge Management (HIKM) 2019 - Sydney, Australia
Duration: 29 Jan 201931 Jan 2019
Conference number: 12th
https://web.archive.org/web/20190329212701/http://hikm.net.au/

Conference

ConferenceAustralasian Workshop on Health Informatics and Knowledge Management (HIKM) 2019
Abbreviated titleHIKM 2019
CountryAustralia
CitySydney
Period29/01/1931/01/19
Internet address

Keywords

  • Cross-layer Security
  • Data Provenance.
  • Healthcare
  • Internet of Things (IoT)
  • Security Analysis
  • Security Requirements
  • Trust

Cite this

Jaigirdar, F. T., Rudolph, C., & Bain, C. (2019). "Can I trust the data I see?": a physician's concern on medical data in IoT health architectures. In Y. Wang, & D. Patterson (Eds.), ACSW'19 - Proceedings of the Australasian Computer Science Week Multiconference: Sydney, NSW, Australia — January 29 - 31, 2019 [27] New York NY USA: Association for Computing Machinery (ACM). https://doi.org/10.1145/3290688.3290731
Jaigirdar, Fariha Tasmin ; Rudolph, Carsten ; Bain, Chris. / "Can I trust the data I see?" : a physician's concern on medical data in IoT health architectures. ACSW'19 - Proceedings of the Australasian Computer Science Week Multiconference: Sydney, NSW, Australia — January 29 - 31, 2019. editor / Ying Wang ; Dale Patterson. New York NY USA : Association for Computing Machinery (ACM), 2019.
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abstract = "With the increasing advancement of Internet of Things (IoT) enabled systems, smart medical devices open numerous opportunities for the healthcare sector. The success of using such devices in the healthcare industry depends strongly on secured and reliable medical data transmission. Physicians diagnose that data and prescribe medicines and/or give guidelines/instructions/treatment plans for the patients. Therefore, a physician is always concerned about the medical data trustworthiness, because if it is not guaranteed, a savior can become an involuntary foe! This paper analyses two different scenarios to understand the real-life consequences in IoT-based healthcare (IoT-Health) application. Appropriate sequence diagrams for both scenarios show data movement as a basis for determining necessary security requirements in each layer of IoT-Health. We analyse the individual entities of the overall system and develop a system-wide view of trust in IoT-Health. The security analysis pinpoints the research gap in end-to-end trust and indicates the necessity to treat the whole IoT-Health system as an integrated entity. This study highlights the importance of integrated cross-layer security solutions that can deal with the heterogeneous security architectures of IoT healthcare system and finally identifies a possible solution for the open question raised in the security analysis with appropriate future research directions.",
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Jaigirdar, FT, Rudolph, C & Bain, C 2019, "Can I trust the data I see?": a physician's concern on medical data in IoT health architectures. in Y Wang & D Patterson (eds), ACSW'19 - Proceedings of the Australasian Computer Science Week Multiconference: Sydney, NSW, Australia — January 29 - 31, 2019., 27, Association for Computing Machinery (ACM), New York NY USA, Australasian Workshop on Health Informatics and Knowledge Management (HIKM) 2019, Sydney, Australia, 29/01/19. https://doi.org/10.1145/3290688.3290731

"Can I trust the data I see?" : a physician's concern on medical data in IoT health architectures. / Jaigirdar, Fariha Tasmin; Rudolph, Carsten; Bain, Chris.

ACSW'19 - Proceedings of the Australasian Computer Science Week Multiconference: Sydney, NSW, Australia — January 29 - 31, 2019. ed. / Ying Wang; Dale Patterson. New York NY USA : Association for Computing Machinery (ACM), 2019. 27.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

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Jaigirdar FT, Rudolph C, Bain C. "Can I trust the data I see?": a physician's concern on medical data in IoT health architectures. In Wang Y, Patterson D, editors, ACSW'19 - Proceedings of the Australasian Computer Science Week Multiconference: Sydney, NSW, Australia — January 29 - 31, 2019. New York NY USA: Association for Computing Machinery (ACM). 2019. 27 https://doi.org/10.1145/3290688.3290731