Treffer: Blockchain and Federated Learning in Edge-Fog-Cloud Computing Environments for Smart Logistics.

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. [ABSTRACT FROM AUTHOR]

المقال يركز على دمج تقنية البلوكشين والتعلم الفيدرالي (FL) ضمن بيئات الحوسبة الحافة-الضباب-السحاب (EFC) لتعزيز اللوجستيات الذكية. يستعرض 134 دراسة بحثية نُشرت بين يناير 2023 ويونيو 2025، مسلطًا الضوء على فوائد هذه التقنيات في تحسين أمان البيانات، والخصوصية، والتتبع في الوقت الحقيقي، وتحسين سلسلة الإمداد. على الرغم من إمكانياتها، لا تزال التحديات مثل قابلية التوسع، وجودة البيانات، والتشغيل البيني، وعقبات التنفيذ تمثل قضايا هامة. يقترح المقال اتجاهات بحثية مستقبلية تهدف إلى تطوير هذه التقنيات ومعالجة التحديات المحددة لإنشاء أنظمة لوجستية ذكية وآمنة. [Extracted from the article]

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