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ChainSCAN: A Blockchain-Based Supply Chain Alerting Framework for Food Safety

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Science of Cyber Security (SciSec 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13580))

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Abstract

Supply Chain Management (SCM) systems provide a digital platform for the supply chain organizations to communicate and exchange information. In the food industry, SCMs provide the essential software components for monitoring food transportation and product handling. However, contemporary SCM systems suffer from non-traceability, non-interoperability and poor resiliency. Global food supply chains are at risks from cyber threats, which will lead to food shortages and poor quality control. In this paper, we present ChainSCAN, a three-layer design of a fully decentralized and blockchain-based SCM system that protects data security, privacy, and remove single point of failures of traditional SCMs. In addition, ChainSCAN provides a transparent environment to protect physical security of assets from stolen and record all activities of the food supply chain. ChainSCAN leverages four smart contracts to automate and regulate interactions of supply chain participants with the ledger, which can enforce the best practices among all supply chain organizations. Furthermore, ChainSCAN contains a notification system that automatically alerts consumers about food recalls and/or potential misbehaviors.

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Notes

  1. 1.

    Source code found in https://github.com/jacastillo8/ChainSCAN.

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Acknowledgments

This research is sponsored by the National Science Foundation (NSF) under Grant No.1812599, and in part by Department of Energy/National Nuclear Security Administration (DOE/NNSA) DE-NA0003985. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of NSF and DOE/NNSA.

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Authors and Affiliations

  1. The University of Texas at San Antonio, San Antonio, TX, 78249, USA

    Jorge Castillo, Kevin Barba & Qian Chen

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  1. Jorge Castillo
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  2. Kevin Barba
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  3. Qian Chen
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Correspondence to Jorge Castillo .

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Editors and Affiliations

  1. University of Aizu, Aizuwakamatsu, Fukushima, Japan

    Chunhua Su

  2. Kyushu University, Fukuoka, Japan

    Kouichi Sakurai

  3. Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China

    Feng Liu

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Castillo, J., Barba, K., Chen, Q. (2022). ChainSCAN: A Blockchain-Based Supply Chain Alerting Framework for Food Safety. In: Su, C., Sakurai, K., Liu, F. (eds) Science of Cyber Security. SciSec 2022. Lecture Notes in Computer Science, vol 13580. Springer, Cham. https://doi.org/10.1007/978-3-031-17551-0_1

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  • DOI: https://doi.org/10.1007/978-3-031-17551-0_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-17550-3

  • Online ISBN: 978-3-031-17551-0

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