无人机
网络拓扑
钥匙(锁)
方案(数学)
计算机安全
计算机科学
欺骗
无线传感器网络
计算机网络
工程类
心理学
数学
遗传学
社会心理学
生物
数学分析
作者
Yawen Tan,Jiajia Liu,Jiadai Wang
出处
期刊:IEEE Transactions on Vehicular Technology
[Institute of Electrical and Electronics Engineers]
日期:2022-08-22
卷期号:71 (12): 13320-13331
被引量:17
标识
DOI:10.1109/tvt.2022.3200339
摘要
Unmanned Aerial Vehicle (UAV) networks, consisting of flexible, low-cost as well as easily deployable UAVs, have attracted intensive research interest recently. Due to different roles of drones in a network, some drones can be recognized as more important than others. For example, in UAV-assisted wireless sensor networks, drones can be used as store-carry and forward nodes to collect data from sensors and aid communications among them. If UAVs that act as the bridge of a large number of sensors are attacked, the production efficiency will be seriously affected. However, existing work concerning about UAV network security seldom noticed the differences among drones, let alone implementing special measures for protecting key drones. Motivated by this, we focus on the security issue of UAV networks from the perspective of key drones' protection. We first analyze the distinctions of attack impacts when adopting different target selection strategies, revealing that key drones exist and it is significantly important to protect them. Then, a topology deception scheme based on software-defined networking is proposed, which can mitigate the attack impact by tempting attackers through our well-designed virtual topologies, leading to their misjudgments on the key drones. Extensive experimental results illustrate that our scheme can effectively deceive attackers and significantly mitigate the impact of targeted attacks.
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