TY - JOUR
T1 - How to Protect Key Drones in Unmanned Aerial Vehicle Networks? An SDN-Based Topology Deception Scheme
AU - Tan, Yawen
AU - Liu, Jiajia
AU - Wang, Jiadai
N1 - Publisher Copyright:
© 1967-2012 IEEE.
PY - 2022/12/1
Y1 - 2022/12/1
N2 - 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.
AB - 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.
KW - Software-defined networking
KW - topology deception
KW - unmanned aerial vehicles
UR - http://www.scopus.com/inward/record.url?scp=85137607621&partnerID=8YFLogxK
U2 - 10.1109/TVT.2022.3200339
DO - 10.1109/TVT.2022.3200339
M3 - 文章
AN - SCOPUS:85137607621
SN - 0018-9545
VL - 71
SP - 13320
EP - 13331
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
IS - 12
ER -