BlockSD-5GNet: Enhancing security of 5G network through blockchain-SDN with ML-based bandwidth prediction

The fifth generation (5G) of mobile communications is the most exciting emerging technology for researchers and scientists to get the full benefit of a network system. However, 5G networks confront massive threats and vulnerabilities including protection, privacy, and secrecy. To face these challenges in the increasingly interconnected Internet of Things (IoT) scenario, we aim to leverage state-of-the-art technologies as software defined networking (SDN) in conjunction with network function virtualization (NFV), blockchain, and machine learning (ML). Indeed, these technologies convey a robust and secure setting in the networking platform enabling to manage several criticalities related to security, privacy, flexibility, and performance. In light of these considerations, in this article, we propose the "BlockSD-5GNet" architecture to efficiently improve the security of a 5G network and to exploit the combined advantages of Blockchain, SDN, NFV, and ML. In the proposed architecture, the SDN helps to manage the network by dividing it into data plane and control plane, while the Blockchain guarantees improved security and confidentiality. Therefore, the "BlockSD-5GNet" architecture can both secure sensitive data and attain reliable data transfer within and between the 5G network-infrastructure planes. Additionally, an ML module is integrated into the SDN controller to estimate network bandwidth and assist the administrator in taking effective decisions and satisfying high-bandwidth demand. We assess the performance of the "BlockSD-5GNet" architecture via an experimental evaluation performed in a simulation environment, and show the effectiveness of the proposed solution in comparison with baseline schemes. Finally, we also demonstrate the capability of different ML models in bandwidth prediction. The present work proposes the "BlockSD-5GNet" architecture aimed at improving the management, security, and privacy of a 5G network by exploiting the combined advantages of stateof-the-art technologies, namely Software Defined Networking, Network Function Virtualization, Blockchain, and Machine Learning. Extensive simulations have shown the effectiveness of the proposed architecture which outperforms various state-of-the-art baselines both in terms of performance (i.e., achievable bandwidth, throughput, and computational delay), robustness (i.e., node failure rate), and bandwidth prediction capability (by means of Machine Learning models). image