Federated blockchained supply chain management: A cybersecurity and privacy framework

Demertzis, Konstantinos; Iliadis, Lazaros; Pimenidis, Elias; Tziritas, Nikolaos; Koziri, Maria; Kikiras, Panagiotis; Tonkin, Michael

Abstract

The complete transformation of the supply chain in a truly integrated and fully automated process, presupposes the continuous and endless collection of digital information from every stage of the production scale. The aim is not only to investigate the current situation, but also the history for every stage of the chain. Given the heterogeneity of the systems involved in the supply chain and the non-institutional interoperability in terms of hardware and software, serious objections arise as to how these systems are digitally secured. An important issue is to ensure privacy and business confidentiality. This paper presents a specialized and technologically up-to-date framework for the protection of digital security, privacy and industrial-business secrecy. At its core is Federated Learning technology, which operates over Blockchain and applies advanced encryption techniques.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 17th International Conference on Artificial Intelligence Applications and Innovations
• Start Date: Jun 22, 2021
• End Date: Jun 27, 2021
• Acceptance Date: May 16, 2021
• Online Publication Date: Jun 22, 2021
• Publication Date: 2021
• Deposit Date: May 27, 2021
• Publicly Available Date: Jun 23, 2023
• Publisher: Springer
• Volume: 627
• Pages: 769-779
• Series Title: IFIP Advances in Information and Communication Technology
• Book Title: Artificial Intelligence Applications and Innovations
• ISBN: 9783030791490
• DOI: https://doi.org/10.1007/978-3-030-79150-6_60
• Keywords: Blockchain; Meta-Learning; Federated Learning; Cyber-Security; Privacy; Industry 40; Supply Chain Management
• Public URL: https://uwe-repository.worktribe.com/output/7426772