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A Blockchain-Based Trust Model for the Internet of Things Supply Chain Management

Accurate data and strategic business processes are crucial to all parties in a supply chain system. However, the absence of mutual trust can create a barrier to implementation. Several studies have shown that supply chains face challenges arising from a lack of trust with respect to the sharing of d...

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Detalles Bibliográficos
Autores principales: Al-Rakhami, Mabrook S., Al-Mashari, Majed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7961540/
https://www.ncbi.nlm.nih.gov/pubmed/33806319
http://dx.doi.org/10.3390/s21051759
Descripción
Sumario:Accurate data and strategic business processes are crucial to all parties in a supply chain system. However, the absence of mutual trust can create a barrier to implementation. Several studies have shown that supply chains face challenges arising from a lack of trust with respect to the sharing of data. How well each party trusts the data they receive can have a profound influence on management decisions. Blockchain technology has been widely used to process cryptocurrency transactions. Recently, it has also proved to be effective in creating trust in the Internet of things (IoT) domain. Blockchain technology can facilitate mutual trust between parties who would otherwise have been doubtful of each other’s data, allowing for more effective and secure sharing of data. However, if the blockchain is not IoT-optimized, companies can experience significant delays and the need for extensive computational capacity. Moreover, there are still some limitations regarding the consensus between the nodes in the traditional consensus approaches. Here, we propose an alternative approach to creating trust in supply chains with diverse IoT elements. Our streamlined trust model simplifies data sharing and reduces computational, storage, and latency requirements while increasing the security of the IoT-based supply chain management. We evaluate the suggested model using simulations and highlight its viability.