Digital Twin Envisioned Secure Air-Ground Integrated Networks: A Blockchain-Based Approach
Minghui Dai, Tianshun Wang, Yang Li, Yuan Wu, Liping Qian, Zhou Su
Abstract
The wide use of unmanned aerial vehicles provides a promising paradigm for improving air-ground services and applications (e.g., urban sensing, disaster relief) in air-ground integrated networks (AGINs). Digital twin (DT), which is an emerging technology that utilizes data, models, and intelligent algorithms to integrate cyber physical networks and digital virtual models, provides a real-time and dynamic simulation platform for strategy optimization and decision making in AGINs. Due to the openness and massive connectivity of AGINs, the security and reliability services in this system become an important issue. In this article, we investigate the DT envisioned secure federated aerial learning for AGINs via an aerial blockchain approach. Specifically, we propose a layered framework of DT envisioned AGINs, which comprises the construction segment, communication segment, aggregation segment, analysis segment, and operation segment. Based on this framework, we offer the applications of the proposed DT envisioned AGINs. To guarantee the security of data transmission in AGINs, we investigate the aerial blockchain-based approach for ensuring data security. Furthermore, we provide a case study of DT envisioned secure federated aerial computing in AGINs to validate the effectiveness of the proposed approach through designing the aerial blockchain and training model.