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UAVCAN Dataset Description

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arxiv 2212.09268 v2 pith:OWIDNUSB submitted 2022-12-19 cs.CR

Dongsung Kim , Yuchan Song , Soonhyeon Kwon , Haerin Kim , Jeong Do Yoo , Huy Kang Kim This is my paper · ORCID
classification cs.CR
keywords attackdatatotaluavcananomalyattacksbuiltcarried
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We collected attack data from unmanned vehicles using the UAVCAN protocol, and public and described technical documents. A testbed was built with a drone using PX4, and a total of three attacks, Flooding, Fuzzy, and Replay, were performed. The attack was carried out in a total of 10 scenarios. We expect that the attack data will help develop technologies such as anomaly detection to solve the security threat problem of drones.

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Cited by 1 Pith paper

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  1. Graph-Powered Defense: Controller Area Network Intrusion Detection for Unmanned Aerial Vehicles

    cs.AI 2024-12 reject novelty 5.0 of 10

    Graph-based models on UAV CAN bus traffic beat an LSTM in some scenarios, but the transfer ID feature contradicts the protocol-independent claim and several attacks go undetected.

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