Enabling Trustworthy Federated Learning in Industrial IoT: Bridging the Gap Between Interpretability and Robustness

Federated Learning (FL) represents a paradigm shift in machine learning, allowing collaborative model training while keeping data localized. This approach is particularly pertinent in the Industrial Internet of Things (IIoT) context, where data privacy, security, and efficient utilization of distributed resources are paramount. The essence of FL in IIoT lies in its ability to learn from diverse, distributed data sources without requiring central data storage, thus enhancing privacy and reducing communication overheads. However, despite its potential, several challenges impede the widespread adoption of FL in IIoT, notably in ensuring interpretability and robustness. This article focuses on enabling trustworthy FL in IIoT by bridging the gap between interpretability and robustness, which is crucial for enhancing trust, improving decision-making, and ensuring compliance with regulations. Moreover, the design strategies summarized in this article ensure that FL systems in IIoT are transparent and reliable, vital in industrial settings where decisions have significant safety and economic impacts. The case studies in the IIoT environment driven by trustworthy FL models are provided, wherein the practical insights of trustworthy communications between IIoT systems and their end users are highlighted.

Blockchain-Based Security Architecture for Unmanned Aerial Vehicles in B5G/6G Services and Beyond: A Comprehensive Approach

Unmanned Aerial Vehicles (UAVs), previously favored by enthusiasts, have evolved into indispensable tools for effectively managing disasters and responding to emergencies. For example, one of their most critical applications is to provide seamless wireless communication services in remote rural areas. Thus, it is substantial to identify and consider the different security challenges in the research and development associated with advanced UAV-based B5G/6G architectures. Following this requirement, the present study thoroughly examines the security considerations about UAVs in relation to the architectural framework of the 5G/6G system, the technologies that facilitate its operation, and the concerns surrounding privacy. It exhibits security integration at all the protocol stack layers and analyzes the existing mechanisms to secure UAV-based B5G/6G communications and its energy and power optimization factors. Last, this article also summarizes modern technological trends for establishing security and protecting UAV-based systems, along with the open challenges and strategies for future research work.