Civilian Unmanned Aerial Vehicle Vulnerability to GPS Spoofing Attacks

He, Liang; Li, Wei; Guo, Chengjun; Niu, Ruizhao

doi:10.1109/iscid.2014.131

Cited by 17 publications

(5 citation statements)

References 4 publications

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“…He et al 13 proposed a GPS spoofing detection scheme based on signal distortion detection. Because the initial phase of GPS signal and C/A code are relatively stable in the frequency of each modulation level.…”

Section: Methods Based On Physical Characteristics Of Gps Signalmentioning

confidence: 99%

“…But with the discovery of cold start attacks and bypass attacks, the adversary can obtain part of the key information from these attacks, the security of the original cryptosystem can no longer be guaranteed. 13 Hanlon et al 14 design a safe antileak scheme. They set up a secure GPS receiver, both receivers will receive the unknown encrypted GPS signal.…”

Section: Methods Based On Cryptographymentioning

confidence: 99%

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Detection of global positioning system spoofing attack on unmanned aerial vehicle system

Chen

Miao

et al. 2020

Concurrency and Computation

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Most of the existing global positioning system (GPS) spoofing detection schemes are vulnerable to the generative GPS spoofing attack, or require additional auxiliary equipment and extensive signal processing capabilities, leading to defects such as low real-time performance and large communication overhead which are not available for the unmanned aerial vehicle (UAV, also known as drone) system. Therefore, we propose a novel solution which employs information fusion based on the GPS receiver and inertial measurement unit. We use a real-time model of tracking and calculating to derive the current position of the drones which are then contrasted with the position information received by the receiver to verify whether the presence or absence of spoofing attack. Subsequent experimental work shows that, the proposed method can accurately detect the spoof within 8 seconds, with a detection rate (DR) of 98.6%. Compared with the existing schemes, the performance of real-time detecting is improved while the DR is ensured. Even in our worst-case, we detect the spoof within 28 seconds after the UAV system starts its mission.

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Section: Methods Based On Physical Characteristics Of Gps Signalmentioning

confidence: 99%

Section: Methods Based On Cryptographymentioning

confidence: 99%

Detection of global positioning system spoofing attack on unmanned aerial vehicle system

Chen

Miao

et al. 2020

Concurrency and Computation

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“…As early as 2011, Iranian air defence forces used deception jamming technology to capture a US "RQ‐170" unmanned reconnaissance aircraft on the country's eastern border, which was the first time that deception jamming technology was applied in actual combat [22]. Humphrey’s team at Texas State University designed an early satellite navigation signal simulator to realise the settings of spoofing signal delay and spoofing power, which laid the platform foundation for the subsequent advancement of deceptive jamming research [23]. Bertold Van den Bergh analysed the risks posed by off‐the‐shelf civilian GPS jammers to UAVs, described and implemented countermeasures using custom hardware and software, tested the proposed solution under ideal and field conditions, and the results showed that the system achieved good performance with a little additional system cost [24].…”

Section: Related Workmentioning

confidence: 99%

Smart forwarding deceptive jamming distribution optimal algorithm

Tang,

Ding,

et al. 2024

IET Radar Sonar & Navi

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With the frequent occurrence of drone black flying in large stadiums and airports, the requirement of precise electromagnetic interference to achieve unmanned aerial vehicle (UAV) displacement and forced landing in these protected area became urgent. Since traditional suppression jamming will affect normal communication, and forwarding deceptive jamming has coverage hole, a smart forwarding deceptive jamming distribution optimal algorithm (SFDJDO) is proposed. It gives a mapping error scale factor and the optimal distribution of multistation forwarding equivalent mapping to solve the problem of distortion on the mapping scale caused by different distribution methods and reduces the influence of the mapping errors and the differences between the virtual and real point neighborhoods of the jamming source. A comparison of the proposed SFDJDO method to the existing jamming source distribution optimisation method is conducted in the aspect of area mapping and trajectory mapping. The findings reveal that when the GNSS receiver clock bias is within the capture range, SFDJDO demonstrates significant enhancements in mapping precision and jamming success rates.

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“…Some DoS attacks may affect the infotainment system, while others target the CAN bus to disturb the critical parts such as the steering, throttle, and brakes. The ECUs responsible for these parts may be overloaded with DoS attacks, so they fail to initiate commands in real-time to control the vehicle [59][60][61][62].…”

Section: )mentioning

confidence: 99%

A Review: Cybersecurity Challenges and their Solutions in Connected and Autonomous Vehicles (CAVs)

Saeed,

Masood,

Khan

2023

JAREE

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Connected and Autonomous Vehicles (CAVs) are a crucial breakthrough in the automotive industry and a magnificent step toward a safe, secure, and intelligent transportation system (ITS). CAVs offer tremendous benefits to our society and environment, such as mitigation of traffic accidents, reduction in traffic congestion, fewer emissions of harmful gases, etc. However, emerging automotive technology also has some serious safety concerns. One of them is cyber security. Conventional vehicles are less prone to cyber-attacks, but CAVs are more susceptible to such events as they communicate with the surrounding infrastructure and other vehicles. To gather data for a better perception of their surroundings, CAVs are outfitted with state-of-the-art sensors and modules like LiDAR, GPS, RADAR, onboard computers, cameras, etc. Hackers, terrorist organizations, and vandals can manipulate this sensor data or may access the primary control by cyber-attack, which may result in enormous fatalities. The automotive industry must put up a rigid framework against cyber invasions to make CAVs a more reliable and secure means of transportation. This paper provides an overview of cybersecurity challenges in CAVs at the module and software levels. The sources of active and passive threats are analyzed. Finally, a feasible solution is recommended to cope with such threats

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Civilian Unmanned Aerial Vehicle Vulnerability to GPS Spoofing Attacks

Cited by 17 publications

References 4 publications

Detection of global positioning system spoofing attack on unmanned aerial vehicle system

Detection of global positioning system spoofing attack on unmanned aerial vehicle system

Smart forwarding deceptive jamming distribution optimal algorithm

A Review: Cybersecurity Challenges and their Solutions in Connected and Autonomous Vehicles (CAVs)

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