An efficient UAV hijacking detection method using onboard inertial measurement unit

With the fast growth of civil drones, their security problems meet significant challenges. A commercial drone may be hijacked by a GPS-spoofing attack for illegal activities, such as terrorist attacks. The target of this article is to develop a technique that only uses onboard gyroscopes to determin...

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Main Authors: Feng, Zhiwei, Guan, Nan, Lv, Mingsong, Liu, Weichen, Deng, Qingxu, Liu, Xue, Yi, Wang
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2020
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Online Access:https://hdl.handle.net/10356/144758
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1447582020-11-23T08:06:11Z An efficient UAV hijacking detection method using onboard inertial measurement unit Feng, Zhiwei Guan, Nan Lv, Mingsong Liu, Weichen Deng, Qingxu Liu, Xue Yi, Wang School of Computer Science and Engineering Engineering::Computer science and engineering Detection Methods Drones With the fast growth of civil drones, their security problems meet significant challenges. A commercial drone may be hijacked by a GPS-spoofing attack for illegal activities, such as terrorist attacks. The target of this article is to develop a technique that only uses onboard gyroscopes to determine whether a drone has been hijacked. Ideally, GPS data and the angular velocities measured by gyroscopes can be used to estimate the acceleration of a drone, which can be further compared with the measurement of the accelerometer to detect whether a drone has been hijacked. However, the detection results may not always be accurate due to some calculation and measurement errors, especially when no hijacking occurs in curve trajectory situations. To overcome this, in this article, we propose a novel and simple method to detect hijacking only based on gyroscopes’ measurements and GPS data, without using any accelerometer in the detection procedure. The computational complexity of our method is very low, which is suitable to be implemented in the drones with micro-controllers. On the other hand, the proposed method does not rely on any accelerometer to detect attacks, which means it receives less information in the detection procedure and may reduce the results accuracy in some special situations. While the previous method can compensate for this flaw, the high detection results also can be guaranteed by using the above two methods. Experiments with a quad-rotor drone are conducted to show the effectiveness of the proposed method and the combination method. 2020-11-23T08:06:11Z 2020-11-23T08:06:11Z 2018 Journal Article Feng, Z., Guan, N., Lv, M., Liu, W., Deng, Q., Liu, X., & Yi, W. (2018). An efficient UAV hijacking detection method using onboard inertial measurement unit. ACM Transactions on Embedded Computing Systems, 17(6), 96-. doi:10.1145/3289390 1539-9087 https://hdl.handle.net/10356/144758 10.1145/3289390 6 17 en ACM Transactions on Embedded Computing Systems © 2018 Association for Computing Machinery. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering
Detection Methods
Drones
spellingShingle Engineering::Computer science and engineering
Detection Methods
Drones
Feng, Zhiwei
Guan, Nan
Lv, Mingsong
Liu, Weichen
Deng, Qingxu
Liu, Xue
Yi, Wang
An efficient UAV hijacking detection method using onboard inertial measurement unit
description With the fast growth of civil drones, their security problems meet significant challenges. A commercial drone may be hijacked by a GPS-spoofing attack for illegal activities, such as terrorist attacks. The target of this article is to develop a technique that only uses onboard gyroscopes to determine whether a drone has been hijacked. Ideally, GPS data and the angular velocities measured by gyroscopes can be used to estimate the acceleration of a drone, which can be further compared with the measurement of the accelerometer to detect whether a drone has been hijacked. However, the detection results may not always be accurate due to some calculation and measurement errors, especially when no hijacking occurs in curve trajectory situations. To overcome this, in this article, we propose a novel and simple method to detect hijacking only based on gyroscopes’ measurements and GPS data, without using any accelerometer in the detection procedure. The computational complexity of our method is very low, which is suitable to be implemented in the drones with micro-controllers. On the other hand, the proposed method does not rely on any accelerometer to detect attacks, which means it receives less information in the detection procedure and may reduce the results accuracy in some special situations. While the previous method can compensate for this flaw, the high detection results also can be guaranteed by using the above two methods. Experiments with a quad-rotor drone are conducted to show the effectiveness of the proposed method and the combination method.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Feng, Zhiwei
Guan, Nan
Lv, Mingsong
Liu, Weichen
Deng, Qingxu
Liu, Xue
Yi, Wang
format Article
author Feng, Zhiwei
Guan, Nan
Lv, Mingsong
Liu, Weichen
Deng, Qingxu
Liu, Xue
Yi, Wang
author_sort Feng, Zhiwei
title An efficient UAV hijacking detection method using onboard inertial measurement unit
title_short An efficient UAV hijacking detection method using onboard inertial measurement unit
title_full An efficient UAV hijacking detection method using onboard inertial measurement unit
title_fullStr An efficient UAV hijacking detection method using onboard inertial measurement unit
title_full_unstemmed An efficient UAV hijacking detection method using onboard inertial measurement unit
title_sort efficient uav hijacking detection method using onboard inertial measurement unit
publishDate 2020
url https://hdl.handle.net/10356/144758
_version_ 1688654648184930304