Effect of Spoofing on Unmanned Aerial Vehicle using Counterfeited GPS Signal

Seo, Seong-Hun; Lee, Byung-Hyun; Im, Sung-Hyuck; Jee, Gyu-In

doi:10.11003/jpnt.2015.4.2.057

Cited by 64 publications

(24 citation statements)

References 2 publications

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“…, ω N }, according to the value of ς i (t). The idea behind introducing (7) is that by analyzing the output signals, we can decide about the attack occurrence by checking if the received output is compatible with the introduced signals or not.…”

Section: B Signal Generationmentioning

confidence: 99%

“…Due to the importance of assessing the vulnerabilities of UAVs, and developing new defense mechanisms, which could help in mitigating them, simulations of cyber attacks on UAVs are being executed [6]. [7] performed a GPS spoofing attack on a quadrotor, resulting in the UAV landing at an incorrect location. A deauthentication attack on a quadrotor was used by [8] to demonstrate its vulnerability, resulting in the loss of control by the operator.…”

Section: Introductionmentioning

confidence: 99%

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Frequency-based detection of replay attacks: application to a quadrotor UAV

Sánchez

Rotondo

Vidal

et al. 2019

2019 8th International Conference on Systems and Control (ICSC)

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Unmanned aerial vehicles (UAVs) are reported to be highly exposed as possible targets of cyber attacks, due to their strong strategic and economic value, and their increasing use in a wide range of operations. Among the most critical cyber attacks, replay attacks are performed by replacing the real data coming from the sensors with previously recorded data, causing deterioration of the control system's performance and potentially allowing other types of attacks without being discovered. The main contribution of this paper is to investigate the applicability of a frequency-based detection method, which uses a sinusoidal signal with a time-varying frequency as authentication signal, to a UAV affected by replay attacks. The effectiveness of the method is illustrated through simulation scenarios.

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Section: B Signal Generationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Frequency-based detection of replay attacks: application to a quadrotor UAV

Sánchez

Rotondo

Vidal

et al. 2019

2019 8th International Conference on Systems and Control (ICSC)

View full text Add to dashboard Cite

show abstract

“…The team found that, when spoofing signals were implanted, not only DLL and PLL tracking loops generate errors, but also pseudo moments could occur linear changes, which in turn led to the wrong navigation results and time offsets. Seong-Hun Seo et al, of Konkuk University in 2015, set up their software-based GNSS signal generator and conducted satellite navigation deceptive attack experiments against UAV [13]. The experimental results showed that despite the specific spoofing protection capabilities of the UAV, the deceptive attack method could accurately cheat the UAV to the target point when the attackers get the grasp of the movement state of the UAV.…”

Section: Introductionmentioning

confidence: 99%

Spoofing Control Strategy for Precise Position Offset Based on INS/GNSS Tightly Coupled Navigation

et al. 2020

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To deceive Inertial Navigation System(INS)/Global Navigation Satellite System(GNSS) integrated navigation terminals, the entry point is still to inject GNSS spoofing signals to the target system. However, the spoofing control strategy in integrated navigation mode for particular tasks such as fixedpoint capture or directional drive needs further research. Whether applying GNSS spoofing attacks or not, the Kalman filter correction gain matrix element in the tightly coupled navigation system always maintains its stability, which gives us valuable clues to develop an effective spoofing attack. On this basis, this article focuses on the feasibility and operability of spoofing attacks under tightly coupled navigation conditions and innovatively proposes a spoofing control strategy that can achieve accurate position offsets: Specific spoofing signals are implanted to the target tightly coupled navigation terminal at the beginning of the spoofing attack. The amounts of pseudo-range spoofing signals corresponding to different satellites are respectively the projections of the position increments to be deceived on the sight vector of the integrated navigation terminal to each satellite. Simulation experiments and tightly coupled navigation terminal experiments verify the correctness and effectiveness of the spoofing control strategy.

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“…Precise aircraft navigation information such as velocity is the basis of the stability control of the UAV [1][2][3][4][5]. The most commonly techniques used to obtain vehicle velocity include the inertial navigation system (INS) [6][7][8], global position system (GPS) [9,10], geomagnetic navigation and a GPS/INS [11][12][13] integrated navigation system. However, the methods mentioned above have problems such as integral and cumulative error, signal loss and the possibility to be interfered by continuously changing electromagnetic signal.…”

Section: Introductionmentioning

confidence: 99%

An Improved Optical Flow Algorithm Based on Mask-R-CNN and K-Means for Velocity Calculation

et al. 2019

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Aiming at enhancing the accuracy and reliability of velocity calculation in vision navigation, an improved method is proposed in this paper. The method integrates Mask-R-CNN (Mask Region-based Convolutional Neural Network) and K-Means with the pyramid Lucas Kanade algorithm in order to reduce the harmful effect of moving objects on velocity calculation. Firstly, Mask-R-CNN is used to recognize the objects which have motions relative to the ground and covers them with masks to enhance the similarity between pixels and to reduce the impacts of the noisy moving pixels. Then, the pyramid Lucas Kanade algorithm is used to calculate the optical flow value. Finally, the value is clustered by the K-Means algorithm to abandon the outliers, and vehicle velocity is calculated by the processed optical flow. The prominent advantages of the proposed algorithm are (i) decreasing the bad impacts to velocity calculation, due to the objects which have relative motions; (ii) obtaining the correct optical flow sets and velocity calculation outputs with less fluctuation; and (iii) the applicability enhancement of the optical flow algorithm in complex navigation environment. The proposed algorithm is tested by actual experiments. Results with superior precision and reliability show the feasibility and effectiveness of the proposed method for vehicle velocity calculation in vision navigation system.

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Effect of Spoofing on Unmanned Aerial Vehicle using Counterfeited GPS Signal

Cited by 64 publications

References 2 publications

Frequency-based detection of replay attacks: application to a quadrotor UAV

Frequency-based detection of replay attacks: application to a quadrotor UAV

Spoofing Control Strategy for Precise Position Offset Based on INS/GNSS Tightly Coupled Navigation

An Improved Optical Flow Algorithm Based on Mask-R-CNN and K-Means for Velocity Calculation

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