ESCM: An Efficient and Secure Communication Mechanism for UAV Networks
Document Type
Article
Publication Title
IEEE Transactions on Network and Service Management
Abstract
UAV (unmanned aerial vehicle) is rapidly gaining traction in various human activities and has become an integral component of the satellite-air-ground-sea (SAGS) integrated network. As high-speed moving objects, UAVs not only have extremely strict requirements for communication delay, but also cannot be maliciously controlled as a weapon by the attacker. Therefore, it is necessary to design an efficient and secure communication mechanism (ESCM) for the UAV network (a mobile ad hoc network composed of multiple UAVs). For high efficiency, ESCM provides a routing protocol based on the artificial bee colony (ABC) algorithm to accelerate communications between UAVs. Meanwhile, we use blockchain to guarantee the security of UAV networks. However, blockchain has unstable links in high-mobility networks resulting in low consensus efficiency and high communication overhead. Consequently, ESCM introduces digital twin (DT), which transforms the UAV network into a static network by mapping UAVs from the physical world into Cyberspace. This virtual UAV network is called CyberUAV. Then, in CyberUAV, we design a blockchain consensus based on network coding, named Proof of Network Coding (PoNC). Analysis and simulation show that the above modules in ESCM have advantages over existing schemes. Through ablation studies, we demonstrate that these modules are indispensable for efficient and secure communication of UAV networks.
DOI
10.1109/TNSM.2024.3357824
Publication Date
1-1-2024
Keywords
Autonomous aerial vehicles, blockchain consensus, Blockchains, Consensus algorithm, digital twin, Drones, network coding, Routing, routing protocol, Routing protocols, Security, UAV networks
Recommended Citation
H. Luo et al., "ESCM: An Efficient and Secure Communication Mechanism for UAV Networks," IEEE Transactions on Network and Service Management, Jan 2024.
The definitive version is available at https://doi.org/10.1109/TNSM.2024.3357824