On the ICN-IoT with federated learning integration of communication: : Concepts, security-privacy issues, applications, and future perspectives

The individual and integration use of the Internet of Things (IoT), Information-Centric Networking (ICN), and Federated Learning (FL) have recently been used in several network-related scenarios and have consequently experienced a growing interest in the research community. Federated learning addresses the privacy and security issues of the IoT data in a decentralized manner. Also, it can be capable of training the multiple learning algorithms through local content except for exchanging data through intelligent Artificial Intelligence (AI)-based algorithms. Moreover, in ICN, the content is retrieved and stored based on the content name rather than the content location address. On the other hand, it is challenging to support the massive IoT devices by the fifth generation (5G) mobile-cellular networks. Therefore, the cellular 6G networks are expected to increase the connection capabilities by 10–100 times over 5G, which necessitates a convergence of Communication, Computing, and Caching (3C). At the same time, the in-network caching capabilities of ICN can be attractive features for IoT networks. IoT aspires to link anybody and/or everything at any time and location. However, integrating IoT with different areas is a new academic topic and is still in its infancy. As a result, this research highlights the potential of ICN for IoTs by conducting an exhaustive literature review. This work provides a comprehensive survey regarding these three recent research trends (i.e., FL, IoT, and ICN) and reviews the related state-of-the-art literature. We first describe the main features of each technology and discuss their most common and used variants. Furthermore, we envision the integration of such technologies to take advantage efficiently. Indeed, we consider their group-wise (FL-ICN-IoT) utilization based on the need for more robust security and privacy. Additionally, we cover the application fields of these technologies both individually and combinedly. Finally, we discuss the open issues of the reviewed research and describe potential directions for future avenues regarding integrating IoT, ICN, and FL technologies.