A machine learning based attack in UAV communication networks

Xiao Chun Chen, Yu Jia Chen

研究成果: 書貢獻/報告類型會議論文篇章同行評審

5 引文 斯高帕斯(Scopus)

摘要

With the advantages of agility and mobility, unmanned aerial vehicles (UAVs) have been widely applied for various civil and military missions. To dynamically control and monitor UAV, it is necessary to broadcast their location information. However, flying in the aerial environment and the fixed operation location also make UAV communications more vulnerable to privacy attacks. In this paper, we present the machine learning (ML)-based attack of UAV-based wireless networks when an attacker can obtain both plaintext and ciphertext. The collected plaintext-ciphertext pairs can be used to train an ML classifier which can help decrypt the UAV messages. By simulations, we show that a simple neural network (NN) can decrypt UAV location data with high probability. Finally, we conclude the work and present a network coding based encryption scheme as our future research direction.

原文???core.languages.en_GB???
主出版物標題2019 IEEE 90th Vehicular Technology Conference, VTC 2019 Fall - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781728112206
DOIs
出版狀態已出版 - 9月 2019
事件90th IEEE Vehicular Technology Conference, VTC 2019 Fall - Honolulu, United States
持續時間: 22 9月 201925 9月 2019

出版系列

名字IEEE Vehicular Technology Conference
2019-September
ISSN(列印)1550-2252

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???90th IEEE Vehicular Technology Conference, VTC 2019 Fall
國家/地區United States
城市Honolulu
期間22/09/1925/09/19

指紋

深入研究「A machine learning based attack in UAV communication networks」主題。共同形成了獨特的指紋。

引用此