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A Blockchain Secured Pharmaceutical Distribution System to Fight Counterfeiting.
Zoughalian, Kavyan; Marchang, Jims; Ghita, Bogdan.
  • Zoughalian K; Computing Department, Sheffield Hallam University, Sheffield S1 1WB, UK.
  • Marchang J; Computing Department, and Advanced Wellbeing Research Centre, Sheffield Hallam University, Sheffield S1 1WB, UK.
  • Ghita B; Computing Department, Plymouth University, Plymouth PL4 8AA, UK.
Int J Environ Res Public Health ; 19(7)2022 03 30.
Article in English | MEDLINE | ID: covidwho-1785638
ABSTRACT
Counterfeiting drugs has been a global concern for years. Considering the lack of transparency within the current pharmaceutical distribution system, research has shown that blockchain technology is a promising solution for an improved supply chain system. This study aims to explore the current solution proposals for distribution systems using blockchain technology. Based on a literature review on currently proposed solutions, it is identified that the secrecy of the data within the system and nodes' reputation in decision making has not been considered. The proposed prototype uses a zero-knowledge proof protocol to ensure the integrity of the distributed data. It uses the Markov model to track each node's 'reputation score' based on their interactions to predict the reliability of the nodes in consensus decision making. Analysis of the prototype demonstrates a reliable method in decision making, which concludes with overall improvements in the system's confidentiality, integrity, and availability. The result indicates that the decision protocol must be significantly considered in a reliable distribution system. It is recommended that the pharmaceutical distribution systems adopt a relevant protocol to design their blockchain solution. Continuous research is required further to increase performance and reliability within blockchain distribution systems.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Blockchain Type of study: Prognostic study / Reviews Language: English Year: 2022 Document Type: Article Affiliation country: Ijerph19074091

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Blockchain Type of study: Prognostic study / Reviews Language: English Year: 2022 Document Type: Article Affiliation country: Ijerph19074091