Cited by 167Blockchain Technology Applications and SecurityInternet of Things and AIIoT and Edge/Fog Computing

Authenticating health activity data using distributed ledger technologies

Open access
Brogan, James, Baskaran, Immanuel, Ramachandran, Navin·2018·Computational and Structural Biotechnology Journal

Abstract

The on-demand digital healthcare ecosystem is on the near horizon. It has the potential to extract a wealth of information from "big data" collected at the population level, to enhance preventive and precision medicine at the patient level. This may improve efficiency and quality while decreasing cost of healthcare delivered by professionals. However, there are still security and privacy issues that need to be addressed before algorithms, data, and models can be mobilized safely at scale. In this paper we discuss how distributed ledger technologies can play a key role in advancing electronic health, by ensuring authenticity and integrity of data generated by wearable and embedded devices. We demonstrate how the Masked Authenticated Messaging extension module of the IOTA protocol can be used to securely share, store, and retrieve encrypted activity data using a tamper-proof distributed ledger.

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Crossref · 10.1016/j.csbj.2018.06.004

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  • The review suggests that management of access control has seen extensive investigation.

    “The review suggests that management of access control (Zheng et al., 2019) has especially seen extensive investigation (Badr et al., 2018;Brogan et al., 2018).”

    From Blockchain in healthcare: A systematic literature review, synthesizing framework and future research agenda (2020) · cites this paper as Brogan et al., 2018

    The Discussion (page unavailable) describes patient-managed authorization keys and granular access controls, so the paper does investigate access control in its own system. It does not say that access-control management has received extensive investigation across the field; its statement that something has been “well studied” concerns authenticated data structures instead. (LLM, conf=0.82)

    Experimental — accuracy not yet measured
  • Prior studies addressed authentic data mobilization, avoidance of data leakage or double spending on storage, and perpetual data preservation.

    “For instance, prior studies have addressed issues pertaining to authentic data mobilization (Brogan et al., 2018), avoidance of data leakage (Zhang et al., 2016;Zhou et al., 2018) or double spending on storage (Rahmadika & Rhee, 2019), and perpetual data preservation (H.Li et al., 2018).”
  • A few studies reported algorithm-specific constraints including lack of mature scheme for PSN-based blockchains and lack of optimized MAM module library.

    “A few studies have reported constraints specific to their developed algorithms, such as a lack of a mature scheme for PSNbased blockchains for healthcare (Zhang et al., 2016), and a lack of an optimized masked authenticated messaging (MAM) module library (Brogan et al., 2018).”
  • Concerns may relate to users' management/mismanagement of authorized private keys.

    “Such concerns may also be related to maintaining the security of the proposed frameworks from the users' perspectives, for example, the users' management or mismanagement of their authorized private keys (Brogan et al., 2018).”
  • In the reviewed literature, relatively less attention has been paid to the prevention of external attacks, such as attacks on sensor data, escrow, and collusion attacks.

    “However, relatively less attention has been paid to the prevention of external attacks, such as attacks on sensor data (Brogan et al., 2018), escrow, and collusion attacks (Guo et al., 2018).”

    From Blockchain in healthcare: A systematic literature review, synthesizing framework and future research agenda (2020) · cites this paper as Brogan et al., 2018

    Brogan et al. describe authenticating data streams from sensors in Theory > Authenticated Data Structures and demonstrate a secure wearable-data transmission system in Results (page numbers unavailable). The passages found when searching for sensor-data attacks and a literature gap do not assess whether prevention of such attacks has received relatively less attention. The escrow and collusion examples are attached to a different citation. (LLM, conf=0.72)

    Experimental — accuracy not yet measured

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References 23 · Cited by 167

Research works printed but not linked: 18

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Authors
Brogan, J., Baskaran, I., & Ramachandran, N.
Affiliations
  • Albert Einstein College of Medicine (US)
  • University College London (GB)
Corresponding author
  • Brogan, James
  • Ramachandran, Navin
Venue
Computational and Structural Biotechnology Journal
Published
2018-01
Volume
16
Pages
257-266
ISSN
2001-0370 (ISSN-L)
OpenAlex
W2883123626
Cited by
167
References
23
Citations by year
2026: 9 · 2025: 8 · 2024: 17 · 2023: 22 · 2022: 27 · 2021: 30 · 2020: 30 · 2019: 22 · 2018: 2
FWCI
33.89
Type
journal article
Language
en
Open access
Locations
  • Computational and Structural Biotechnology Journal (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
  • Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
Keywords
distributed ledger technology, IOTA, wearable devices, embedded devices, data integrity, encrypted data sharing, electronic health records, data privacy, healthcare security

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