Cybersecurity in Supply Chain Systems: The Farm-to-Fork Use Case

Author:

Leligou Helen C.1ORCID,Lakka Alexandra1,Karkazis Panagiotis A.1ORCID,Costa Joao Pita2,Tordera Eva Marin3,Santos Henrique Manuel Dinis4ORCID,Romero Antonio Alvarez5ORCID

Affiliation:

1. Synelixis Solutions S.A., 34100 Chalkida, Greece

2. XLAB, SI-1000 Ljubljana, Slovenia

3. X Lab, Universidad Politecnica de Catalunya, 08034 Barcelona, Spain

4. ALGORITMI R&D Centre, University of Minho, 4710-057 Braga, Portugal

5. Eviden, 28037 Madrid, Spain

Abstract

Modern supply chains comprise an increasing number of actors which deploy different information technology systems that capture information of a diverse nature and diverse sources (from sensors to order information). While the benefits of the automatic exchange of information between these systems have been recognized and have led to their interconnection, protecting the whole supply chain from potential attacks is a challenging issue given the attack proliferation reported in the literature. In this paper, we present the FISHY platform, which anticipates protecting the whole supply chain from potential attacks by (a) adopting novel technologies and approaches including machine learning-based tools to detect security threats and recommend mitigation policies and (b) employing blockchain-based tools to provide evidence of the captured events and suggested policies. This platform is also easily expandable to protect against additional attacks in the future. We experiment with this platform in the farm-to-fork supply chain to prove its operation and capabilities. The results show that the FISHY platform can effectively be used to protect the supply chain and offers high flexibility to its users.

Funder

the EU funded H2020 FISHY Project

Publisher

MDPI AG

Reference17 articles.

1. Karamitsios, K., and Orphanoudakis, T. (2017, January 3–6). Efficient IoT data aggregation for connected health applications. Proceedings of the 2017 IEEE Symposium on Computers and Communications (ISCC), Heraklion, Greece.

2. European Commission (2023, November 07). TERAFLOW [Online]. Available online: https://www.teraflow-h2020.eu/.

3. European Commission (2023, November 07). ENSURESEC [Online]. Available online: https://www.ensuresec.eu/.

4. Experimental quantum secure network with digital signatures and encryption;Yin;Natl. Sci. Rev.,2023

5. Experimental Quantum Communication Overcomes the Rate-Loss Limit without Global Phase Tracking;Zhou;Phys. Rev. Lett.,2023

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