IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i24p16844-d1004622.html

CoviBlock: A Secure Blockchain-Based Smart Healthcare Assisting System

Author

Listed:
  • Bhaskara S. Egala

    (Department of Computer Science and Engineering, SRM University, Andhra Pradesh 522240, India)

  • Ashok K. Pradhan

    (Department of Computer Science and Engineering, SRM University, Andhra Pradesh 522240, India)

  • Shubham Gupta

    (Department of Computer Science and Engineering, SRM University, Andhra Pradesh 522240, India)

  • Kshira Sagar Sahoo

    (Department of Computer Science and Engineering, SRM University, Andhra Pradesh 522240, India
    Department of Computing Science, Umeå University, SE-901 87 Umeå, Sweden)

  • Muhammad Bilal

    (Department of computer Engineering, Hankuk University of Foreign Studies, Yongin-si 17035, Republic of Korea)

  • Kyung-Sup Kwak

    (Department of Information and Communications Engineering, Inha University, Incheon 22212, Republic of Korea)

Abstract

The recent COVID-19 pandemic has underlined the significance of digital health record management systems for pandemic mitigation. Existing smart healthcare systems (SHSs) fail to preserve system-level medical record openness and privacy while including mitigating measures such as testing, tracking, and treating (3T). In addition, current centralised compute architectures are susceptible to denial of service assaults because of DDoS or bottleneck difficulties. In addition, these current SHSs are susceptible to leakage of sensitive data, unauthorised data modification, and non-repudiation. In centralised models of the current system, a third party controls the data, and data owners may not have total control over their data. The Coviblock, a novel, decentralised, blockchain-based smart healthcare assistance system, is proposed in this study to support medical record privacy and security in the pandemic mitigation process without sacrificing system usability. The Coviblock ensures system-level openness and trustworthiness in the administration and use of medical records. Edge computing and the InterPlanetary File System (IPFS) are recommended as part of a decentralised distributed storage system (DDSS) to reduce the latency and the cost of data operations on the blockchain (IPFS). Using blockchain ledgers, the DDSS ensures system-level transparency and event traceability in the administration of medical records. A distributed, decentralised resource access control mechanism (DDRAC) is also proposed to guarantee the secrecy and privacy of DDSS data. To confirm the Coviblock’s real-time behaviour on an Ethereum test network, a prototype of the technology is constructed and examined. To demonstrate the benefits of the proposed system, we compare it to current cloud-based health cyber–physical systems (H-CPSs) with blockchain. According to the experimental research, the Coviblock maintains the same level of security and privacy as existing H-CPSs while performing considerably better. Lastly, the suggested system greatly reduces latency in operations, such as 32 milliseconds (ms) to produce a new record, 29 ms to update vaccination data, and 27 ms to validate a given certificate through the DDSS.

Suggested Citation

  • Bhaskara S. Egala & Ashok K. Pradhan & Shubham Gupta & Kshira Sagar Sahoo & Muhammad Bilal & Kyung-Sup Kwak, 2022. "CoviBlock: A Secure Blockchain-Based Smart Healthcare Assisting System," Sustainability, MDPI, vol. 14(24), pages 1-21, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16844-:d:1004622
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/24/16844/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/24/16844/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yang, Yuwen & Bidkhori, Hoda & Rajgopal, Jayant, 2021. "Optimizing vaccine distribution networks in low and middle-income countries," Omega, Elsevier, vol. 99(C).
    2. Antonio Fusco & Grazia Dicuonzo & Vittorio Dell’Atti & Marco Tatullo, 2020. "Blockchain in Healthcare: Insights on COVID-19," IJERPH, MDPI, vol. 17(19), pages 1-12, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tang, Lianhua & Li, Yantong & Bai, Danyu & Liu, Tao & Coelho, Leandro C., 2022. "Bi-objective optimization for a multi-period COVID-19 vaccination planning problem," Omega, Elsevier, vol. 110(C).
    2. Khalilpoor, Saeedeh & Kamran, Mehdi A. & Solimanpur, Maghsud, 2025. "Resilient COVID-19 vaccine supply chain: An optimization and simulation approach for multi-objective management," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 201(C).
    3. Shakiba Enayati & Haitao Li & James F. Campbell & Deng Pan, 2023. "Multimodal Vaccine Distribution Network Design with Drones," Transportation Science, INFORMS, vol. 57(4), pages 1069-1095, July.
    4. Kochakkashani, Farid & Kayvanfar, Vahid & Haji, Alireza, 2023. "Supply chain planning of vaccine and pharmaceutical clusters under uncertainty: The case of COVID-19," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    5. Gilani, Hani & Sahebi, Hadi, 2022. "A data-driven robust optimization model by cutting hyperplanes on vaccine access uncertainty in COVID-19 vaccine supply chain," Omega, Elsevier, vol. 110(C).
    6. Vincent Charles & Ali Emrouznejad & Tatiana Gherman, 2023. "A critical analysis of the integration of blockchain and artificial intelligence for supply chain," Annals of Operations Research, Springer, vol. 327(1), pages 7-47, August.
    7. Peng Jiang & Jiří Jaromír Klemeš & Yee Van Fan & Xiuju Fu & Yong Mong Bee, 2021. "More Is Not Enough: A Deeper Understanding of the COVID-19 Impacts on Healthcare, Energy and Environment Is Crucial," IJERPH, MDPI, vol. 18(2), pages 1-22, January.
    8. Fadaki, Masih & Abareshi, Ahmad & Far, Shaghayegh Maleki & Lee, Paul Tae-Woo, 2022. "Multi-period vaccine allocation model in a pandemic: A case study of COVID-19 in Australia," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    9. Shaker Ardakani, Elham & Gilani Larimi, Niloofar & Oveysi Nejad, Maryam & Madani Hosseini, Mahsa & Zargoush, Manaf, 2023. "A resilient, robust transformation of healthcare systems to cope with COVID-19 through alternative resources," Omega, Elsevier, vol. 114(C).
    10. Rey, David & Hammad, Ahmed W. & Saberi, Meead, 2023. "Vaccine allocation policy optimization and budget sharing mechanism using reinforcement learning," Omega, Elsevier, vol. 115(C).
    11. Karatas, Mumtaz & Eriskin, Levent, 2023. "Linear and piecewise linear formulations for a hierarchical facility location and sizing problem," Omega, Elsevier, vol. 118(C).
    12. Vahdani, Behnam & Mohammadi, Mehrdad & Thevenin, Simon & Gendreau, Michel & Dolgui, Alexandre & Meyer, Patrick, 2023. "Fair-split distribution of multi-dose vaccines with prioritized age groups and dynamic demand: The case study of COVID-19," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1249-1272.
    13. Yuwen Yang & Jayant Rajgopal, 2021. "Outreach Strategies for Vaccine Distribution: A Multi-period Stochastic Modeling Approach," SN Operations Research Forum, Springer, vol. 2(2), pages 1-26, June.
    14. Yang, Manyi & Qu, Shaojian & Ji, Ying & Peng, Zhisheng, 2025. "Risk management of the vaccine supply chain: Interactions of risk factors and control strategies," Socio-Economic Planning Sciences, Elsevier, vol. 98(C).
    15. Ignacio Rodríguez-Rodríguez & José-Víctor Rodríguez & Niloofar Shirvanizadeh & Andrés Ortiz & Domingo-Javier Pardo-Quiles, 2021. "Applications of Artificial Intelligence, Machine Learning, Big Data and the Internet of Things to the COVID-19 Pandemic: A Scientometric Review Using Text Mining," IJERPH, MDPI, vol. 18(16), pages 1-29, August.
    16. Virginia Milone & Antonio Fusco & Angelamaria De Feo & Marco Tatullo, 2024. "Clinical Impact of “Real World Data” and Blockchain on Public Health: A Scoping Review," IJERPH, MDPI, vol. 21(1), pages 1-14, January.
    17. Eugenia Ama Andoh & Hao Yu, 2023. "A two-stage decision-support approach for improving sustainable last-mile cold chain logistics operations of COVID-19 vaccines," Annals of Operations Research, Springer, vol. 328(1), pages 75-105, September.
    18. Mohammadi, Mehrdad & Dehghan, Milad & Pirayesh, Amir & Dolgui, Alexandre, 2022. "Bi‐objective optimization of a stochastic resilient vaccine distribution network in the context of the COVID‐19 pandemic," Omega, Elsevier, vol. 113(C).
    19. Jahani, Hamed & Abbasi, Babak & Sheu, Jiuh-Biing & Klibi, Walid, 2024. "Supply chain network design with financial considerations: A comprehensive review," European Journal of Operational Research, Elsevier, vol. 312(3), pages 799-839.
    20. Cristina Andrada Costea & Dora Maria Popescu & Alexandra Roman & Ștefan-Ioan Stratul & Petra Șurlin & Marius Negucioiu & Iulia Cristina Micu & Andreea Ciurea & Patricia Ondine Lucaciu & Luminița Lazăr, 2022. "The Impact of the COVID-19 Pandemic on Romanian Postgraduate Periodontal Residency Teaching: Past Experience, Present Imperatives and Future Considerations in a Multicentric Evaluation," IJERPH, MDPI, vol. 19(8), pages 1-14, April.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16844-:d:1004622. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.