The rapid development of technology has led to a wide application of unmanned aerial vehicles (UAVs) in Internet of Things (IoT). Because of their small size and high mobility, UAVs are being used to meet the increasing demands of social services in the realms of communications, sensing, and rescuing.
UAVs are currently being used in city security, inspection of power grids, fire control in tall buildings, base stations, and ships. In addition, they are also being used in logistics, emergency response, medical transport, and scientific research. Because of the potential of its many applications, UAVs are able to connect to 5G UAV airborne communication terminals. These terminals can collect and transmit data over these 5G networks to control beyond-the-line-of-sight (BLOS)flight of UAVs.
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The threats UAVs 5G network face security threats can lead to service disruptions. In this paper, the authors introduce a trust-based security scheme for 5G UAV Communication systems. The architecture of 5G UAV communication system is first presented to improve the communication performance. Second, a trust evaluation scheme for UAVs is developed to evaluate the reliability of UAVs. By introducing the trust threshold, the malicious UAVs will be filtered out from the systems. Third, with the assistance of mobile edge computing (MEC) nodes, the detection scheme based on Q-learning technology is proposed to detect the malicious attacks. The security threats can be detected to protect the security of systems. Finally, simulation results demonstrate the effectiveness of the proposed scheme.
In a nutshell, the main contributions of this work can be summarized as follows:
- Architecture of 5G UAV communication systems: We present a novel 5G UAV communication systems, which consists of a number of UAVs, numerous MEC nodes, a cloud platform, and a secure management platform. The MEC nodes and cloud platform can provide various services for UAVs. The secure management platform is used to manage the behaviors of UAVs.
- Trust evaluation scheme for UAVs: We design a novel trust evaluation scheme for 5G UAV communication systems. The malicious UAVs can be screened out from the systems.
- Detection scheme based on Q-learning: We develop a detection scheme based on Q-learning technology. The malicious attacks can be detected to protect the security of systems.
- Performance effectiveness: We evaluate the proposed scheme by using the extensive simulations. The results demonstrate that the proposed scheme can improve the security performance.
Continue reading “Trust Based Scheme to Protect 5G UAV Communication Networks” to dive into the proposed trust scheme for 5G UAV communications system.
