Exposing Spoofing Attack on Flocking-Based Unmanned Aerial Vehicle Cluster: A Threat to Swarm Intelligence
Joint Authors
Huang, Xinyu
Tian, Yunzhe
He, Yifei
Tong, Endong
Niu, Wenjia
Li, Chenyang
Liu, Jiqiang
Chang, Liang
Source
Security and Communication Networks
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-10
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Information Technology and Computer Science
Abstract EN
With the rapid development of wireless communication technology and intelligent mobile devices, unmanned aerial vehicle (UAV) cluster is becoming increasingly popular in both civilian and military applications.
Recently, a swarm intelligence-based UAV cluster study, aiming to enable efficient and autonomous collaboration, has drawn lots of interest.
However, new security problems may be introduced with such swarm intelligence.
In this work, we perform the first detailed security analysis to a kind of flocking-based UAV cluster with 5 policies, an upgrade version of the well-known Boids model.
Targeting a realistic threat in a source-to-destination flying task, we design a data spoofing strategy and further perform complete vulnerability analysis.
We reveal that such design and implementation are highly vulnerable.
After breaking through the authentication of ad hoc on-demand distance vector (AODV) routing protocol by rushing attack, an attacker can masquerade as the first-arrival UAV within a specific scope of destination and generate data spoofing of arrival status to the following UAVs, so as to interfere with their normal flying paths of destination arrival and cause unexpected arrival delays amid urgent tasks.
Experiments with detailed analysis from the 5-UAV cluster to the 10-UAV cluster are conducted to show specific feature composition-based attack effect and corresponding average delay.
We also discuss promising defense suggestions leveraging the insights from our analysis.
American Psychological Association (APA)
Huang, Xinyu& Tian, Yunzhe& He, Yifei& Tong, Endong& Niu, Wenjia& Li, Chenyang…[et al.]. 2020. Exposing Spoofing Attack on Flocking-Based Unmanned Aerial Vehicle Cluster: A Threat to Swarm Intelligence. Security and Communication Networks،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1208877
Modern Language Association (MLA)
Huang, Xinyu…[et al.]. Exposing Spoofing Attack on Flocking-Based Unmanned Aerial Vehicle Cluster: A Threat to Swarm Intelligence. Security and Communication Networks No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1208877
American Medical Association (AMA)
Huang, Xinyu& Tian, Yunzhe& He, Yifei& Tong, Endong& Niu, Wenjia& Li, Chenyang…[et al.]. Exposing Spoofing Attack on Flocking-Based Unmanned Aerial Vehicle Cluster: A Threat to Swarm Intelligence. Security and Communication Networks. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1208877
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1208877