Efficient drone hijacking detection using onboard motion sensors

Zhiwei Feng, Nan Guan, Mingsong Lv, Weichen Liu, Qingxu Deng, Xue Liu, Wang Yi

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

13 Citations (Scopus)

Abstract

The fast growth of civil drones raises significant security challenges. A legitimate drone may be hijacked by GPS spoofing for illegal activities, such as terrorist attacks. The target of this paper is to develop techniques to let drones detect whether they have been hijacked using onboard motion sensors (accelerometers and gyroscopes). Ideally, the linear acceleration and angular velocity measured by motion sensors can be used to estimate the position of a drone, which can be compared with the position reported by GPS to detect whether the drone has been hijacked. However, the position estimation by motion sensors is very inaccurate due to the significant error accumulation over time. In this paper, we propose a novel method to detect hijacking based on motion sensors measurements and GPS, which overcomes the accumulative error problem. The computational complexity of our method is very low, and thus is suitable to be implemented in the micro-controllers of drones. Experiments with a quad-rotor drone are conducted to show the effectiveness of the proposed method.
Original languageEnglish
Title of host publicationProceedings of the 2017 Design, Automation and Test in Europe, DATE 2017
PublisherIEEE
Pages1414-1419
Number of pages6
ISBN (Electronic)9783981537093
DOIs
Publication statusPublished - 11 May 2017
Event20th Design, Automation and Test in Europe, DATE 2017 - SwissTech Convention Center, Swisstech, Lausanne, Switzerland
Duration: 27 Mar 201731 Mar 2017

Conference

Conference20th Design, Automation and Test in Europe, DATE 2017
Country/TerritorySwitzerland
CitySwisstech, Lausanne
Period27/03/1731/03/17

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality

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