Blockchain and federated learning in edge-fog-cloud computing environments for smart logistics
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Date
2025-07-22
Journal Title
Journal ISSN
Volume Title
Publisher
Mesopotamian Academic Press
Abstract
The rapid growth of smart logistics, driven by IoT devices and data-intensive applications, necessitates secure, scalable, and efficient computing frameworks. As the edge-fog-cloud (EFC) paradigm supports real-time data processing, it faces significant security threats and attacks, including privacy risks, data breaches, and unauthorized access. To address these security threats and attacks, blockchain and federated learning (FL) have gained popularity as potential solutions in EFC computing environments for smart logistics. This survey reviews the current landscape in EFC computing environments for smart logistics, highlighting the existing benefits and challenges identified in 134 research studies published between January 2023 and June 2025. The applications of blockchain and FL demonstrate their ability to enhance data security and privacy, improve real-time tracking and monitoring, and ensure inventory and supply chain optimization. Although these technologies offer promising solutions, challenges such as scalability issues, data quality, interoperability and standardization hinder their effective implementation. The survey suggests future research directions focused on developing advanced blockchain and FL, integrating emerging technologies, developing policies and regulations, fostering collaborative research, and ensuring cross-industry adoption and interoperability. Integrating blockchain and FL within the EFC model offers a transformative path toward building secure, intelligent, and resilient logistics systems.
Description
This paper examines how combining blockchain and federated learning can secure edge-fog-cloud computing frameworks that support smart logistics by protecting data privacy, preventing breaches, and enabling reliable decentralized model training. It highlights scalable, secure communication and resilient machine learning in distributed IoT environments, addressing key cyber threats in modern data-intensive systems. The research supports SDG 9 on industry innovation and infrastructure, SDG 16 on peace, justice, and strong institutions, and SDG 8 on decent work through safer digital operations. It also aligns with Uganda’s NDP IV aspirations on digital transformation
Keywords
Smart Logistics, Edge-Fog-Cloud Computing, Blockchain Technology, Federated Learning, Data Privacy
Citation
Ali, G., Thomas, A., Mijwil, M. M., Al-Mahzoum, K., Sallam, M., Salau, A. O., Adamopoulos, I., Bala, I., Al-jubori, Aseed, Y. R. & Al-jubori, A. Y. R. (2025). Blockchain and federated learning in edge-fog-cloud computing environments for smart logistics. Mesopotamian Journal of CyberSecurity, 5(2), 735-769.