Security situation assessment in UAV swarm networks using TransReSE: A Transformer-ResNeXt-SE based approach

IF 5.8 2区 计算机科学 Q1 TELECOMMUNICATIONS Vehicular Communications Pub Date : 2024-09-04 DOI:10.1016/j.vehcom.2024.100842
Dongmei Zhao , Pengcheng Shen , Xunzhen Han , Shuiguang Zeng
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Abstract

With the rapid development and extensive application of unmanned aerial vehicles (UAVs), the issue of UAV swarm network security has become prominent. To protect the security of UAV swarm networks, effective network security defense measures are crucial. One key aspect is the assessment and monitoring of the network's security situation. However, most existing research focuses on the security of individual UAVs or detecting specific attacks, which fails to provide proactive protection for the network. To address this issue, we propose a UAV swarm network security situation assessment method, which combines the Transformer network with the optimization of the Aggregated Residual Transformations for Deep Neural Networks (ResNeXt) and squeeze-and-excitation (SE) structure (named TransReSE). By using multiple scale-cross convolution kernels, TransReSE can efficiently extract data features and improve situation assessment accuracy through the Transformer network. Experimental results from four public datasets have shown that TransReSE outperforms other schemes in terms of accuracy, recall, and F1. By assessing the value of the swarm network situation and the threat level, we can make faster, more effective decisions and proactively allocate resources to defend against UAV swarm network attacks.

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使用 TransReSE 评估无人机蜂群网络的安全状况:基于 Transformer-ResNeXt-SE 的方法
随着无人机(UAV)的快速发展和广泛应用,无人机蜂群网络安全问题日益突出。要保护无人机蜂群网络的安全,有效的网络安全防御措施至关重要。其中一个关键环节就是对网络安全状况进行评估和监控。然而,现有研究大多关注单个无人机的安全或检测特定攻击,无法为网络提供主动保护。针对这一问题,我们提出了一种无人机蜂群网络安全状况评估方法,该方法将变换器网络与深度神经网络的聚合残差变换(ResNeXt)和挤压激励(SE)结构的优化相结合(命名为 TransReSE)。通过使用多个尺度交叉卷积核,TransReSE 可以有效地提取数据特征,并通过 Transformer 网络提高情况评估的准确性。四个公共数据集的实验结果表明,TransReSE 在准确率、召回率和 F1 方面都优于其他方案。通过评估蜂群网络态势的价值和威胁程度,我们可以做出更快、更有效的决策,并主动分配资源以抵御无人机蜂群网络攻击。
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来源期刊
Vehicular Communications
Vehicular Communications Engineering-Electrical and Electronic Engineering
CiteScore
12.70
自引率
10.40%
发文量
88
审稿时长
62 days
期刊介绍: Vehicular communications is a growing area of communications between vehicles and including roadside communication infrastructure. Advances in wireless communications are making possible sharing of information through real time communications between vehicles and infrastructure. This has led to applications to increase safety of vehicles and communication between passengers and the Internet. Standardization efforts on vehicular communication are also underway to make vehicular transportation safer, greener and easier. The aim of the journal is to publish high quality peer–reviewed papers in the area of vehicular communications. The scope encompasses all types of communications involving vehicles, including vehicle–to–vehicle and vehicle–to–infrastructure. The scope includes (but not limited to) the following topics related to vehicular communications: Vehicle to vehicle and vehicle to infrastructure communications Channel modelling, modulating and coding Congestion Control and scalability issues Protocol design, testing and verification Routing in vehicular networks Security issues and countermeasures Deployment and field testing Reducing energy consumption and enhancing safety of vehicles Wireless in–car networks Data collection and dissemination methods Mobility and handover issues Safety and driver assistance applications UAV Underwater communications Autonomous cooperative driving Social networks Internet of vehicles Standardization of protocols.
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