Cybersecurity in supply chain systems: the Farm-to-Fork use case

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.