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

Abstract

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.

Adaptive synchronous strategy for distributed machine learning

“…In the future, much work remains to be done. For example, validating A2S on a larger machine cluster, validating A2S in a heterogeneous environment, 50 and further improving A2S according to the discussions in Section 6.…”

Creating orthophotos with unmanned aerial vehicles and examining its accuracy and usability in geodetic applications

“…In this study, the flight altitude has been 40 m and the ground sampling distance (GSD) has been 1.3 cm. The flight has been carried out in an area of 4900 m. 2 In the light of the results, it has been observed that the planimetric accuracy of direct georeference for the photogrammetric data produced varies between 30 and 60 cm, when the ground control points are evaluated. Elkhrachy et al 34 aimed to produce high-precision 3D data from images obtained from an UAV.…”

“…Pilot-assisted mapping systems have begun to lose their importance compared to UAV systems due to the low resolution of aerial photographs taken from high altitude flight heights and the high cost of the system. UAV systems, which can meet the accuracy needed in many engineering projects and scientific studies, [1][2][3][4][5][6][7][8][9][10][11] such as disaster management, agricultural and forestry activities, monitoring deformations, planning and architecture of cities, offer users the opportunity to collect data and produce maps for various purposes from this data. 12 Orthophoto maps are one of the products that emerged as a result of the use of the UAV system.…”

“…On the other hand, these rates have been chosen as 85% and 70%, respectively, in forested areas. A digital elevation model and orthophoto of the area of 250,458 m 2 has been produced by processing 461 photos taken from the UAV with the help of Pix4d and Agisoft Photoscan programs. Kılıç et al 27 compared two different platforms by obtaining images with the help of an UAV and an aerial camera aircraft in the Isparta‐Aksu region.…”

zkChain: A privacy‐preserving model based on zk‐SNARKs and hash chain for efficient transfer of assets

“…With the help of core technologies such as distributed ledgers, asymmetric encryption, smart contracts, and consensus mechanisms, blockchain can realize functions such as point-to-point, anonymity, traceability, and anti-tampering, ensuring the credibility and security of data in a distributed environment. 1,2 With the development of core technologies, a mature blockchain technology system has been formed and applied to Internet of Things (IoT), [3][4][5][6] digital finance, 7 edge computing, 8 artificial intelligence (AI), [9][10][11][12][13][14] supply chain management (SCM) 15 and other fields. However, privacy attacks are still the core problem hindering the popularization and application of blockchain.…”