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http://dx.doi.org/10.13089/JKIISC.2022.32.1.39

Sequence Based Anomaly Detection System for Unmanned Aerial Vehicle  

Seo, Kang Uk (School of Cybersecurity, Korea University)
Kim, Huy Kang (School of Cybersecurity, Korea University)
Publication Information
Journal of the Korea Institute of Information Security & Cryptology / v.32, no.1, 2022 , pp. 39-48 More about this Journal
Abstract
In this paper, we propose an anomaly detection system (ADS) to detect anomalies of the in-vehicle network for unmanned aerial vehicle (UAV). The proposed ADS detects the anomalies by measuring the similarity of status messages sequences periodically sent by the UAV to the ground control system. We defined three types of malicious message injection attacks that can be performed on the in-vehicle network of UAV and simulated those attack techniques in the Pixhawk4 quadcopter. The proposed ADS can detect abnormal sequences with accuracy of higher than 96%.
Keywords
Anomaly detection system; Sequence data; Unmanned aerial vehicle;
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