• Journal of Positioning, Navigation, and Timing
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• v.10 no.3
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• pp.169-177
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• 2021

In this paper, we propose a novel global navigation satellite system (GNSS) spoofing detection technique through an array antenna-based direction of arrival (DoA) estimation of satellite and spoofer. Specifically, we consider a sophisticated GNSS spoofing attack scenario where the spoofer can accurately mimic the multiple pseudo-random number (PRN) signals since the spoofer has its own GNSS receiver and knows the location of the target receiver in advance. The target GNSS receiver precisely estimates the DoA of all PRN signals using compressed sensing-based orthogonal matching pursuit (OMP) even with a small number of samples, and it performs spoofing detection from the DoA estimation results of all PRN signals. In addition, considering the initial situation of a sophisticated spoofing attack scenario, we designed the algorithm to have high spoofing detection performance regardless of the relative spoofing signal power. Therefore, we do not consider the assumption in which the power of the spoofing signal is about 3 dB greater than that of the authentic signal. Then, we introduce design parameters to get high true detection probability and low false alarm probability in tandem by considering the condition for the presence of signal sources and the proximity of the DoA between authentic signals. Through computer simulations, we compare the DoA estimation performance between the conventional signal direction estimation method and the OMP algorithm in few samples. Finally, we show in the sophisticated spoofing attack scenario that the proposed spoofing detection technique using OMP-based estimated DoA of all PRN signals outperforms the conventional spoofing detection scheme in terms of true detection and false alarm probability.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.4
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• pp.173-180
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• 2015

In this study, an algorithm that detects a spoofing signal for a GPS L1 signal was proposed, and the performance was verified through RF spoofing signal simulation. The proposed algorithm determines the reception of a spoofing signal by detecting a correlation distortion of GPS L1 C/A code caused by the spoofing signal. To detect the correlation distortion, a detection criterion of a spoofing signal was derived from the relationship among the Early, Prompt, and Late tap correlation values of a receiver correlator; and a detection threshold was calculated from the false alarm probability of spoofing signal detection. In this study, an RF spoofing environment was built using the GSS 8000 simulator (Spirent). For the RF spoofing signal generated from the simulator, the RF spoofing environment was verified using the commercial receiver DL-V3 (Novatel Inc.). To verify the performance of the proposed algorithm, the RF signal was stored as IF band data using a USRP signal collector (NI) so that the data could be processed by a CNU software receiver (software defined radio). For the performance of the proposed algorithm, results were obtained using the correlation value of the software receiver, and the performance was verified through the detection of a spoofing signal and the detection time of a spoofing signal.

• Journal of Satellite, Information and Communications
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• v.8 no.2
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• pp.29-35
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• 2013

In this paper, we investigate the type and detection methode of spoofing attack, and then analyze the performance of spoofing detection algorithm in GPS L1 signal through the simulation. Generally spoofer is different from the jammer, because the receiver can be operated and not. In case of spoofing the GPS receiver is hard to recognize the spoofing attack and can be operated normally without stopping because the spoofing signal is the mimic GPS signal. To evaluate the performance of spoofing detection algorithm, both the software based spoofing and GPS signal generator and the software based GPS receiver are implemented. In paper, we can check that spoofing signal can affect to the DLL and PLL tracking loop because code delay and doppler frequency of spoofing. The spoofing detection algorithm has been implemented using the pseudorange, signal strength and navigation solution of GPS receiver and proposed algorithm can effectively detect the spoofing signal.

• Journal of Advanced Navigation Technology
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• v.18 no.1
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• pp.7-13
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• 2014

In this paper, an effect on a GPS receiver by spoofing signal is analyzed and a GPS spoofing signal detection algorithm for GPS L1 C/A spoofing signal is proposed. A proposed detection algorithm monitors the correlation function distortion by the spoofing signal. If detected distortion is over a detection threshold, we can determine that the spoofing signal is received. The detection threshold is calculated from the statistical characteristics of a thermal noise. For verifying the suggested algorithm, a MATLAB-based simulation platform is implemented. This platform has functionalities to track GPS signal and measure the correlation values. By using this platform, the correlation function distortion by spoofing signal is observed. Also a performance of the algorithm proposed in this paper is applied and confirm the detection of a spoofing signal.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.2
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• pp.101-111
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• 2023

Many spoofing detection studies have been conducted to cope with the most difficult types of deception among various disturbances of GPS, such as jamming, spoofing, and meaconing. In this paper, we propose a spoofing detection scheme based on elevation masked-relative received power between GPS L1 and L2 signals in a system using a multi-band array antenna. The proposed scheme focuses on enabling spoofing to be normally detected and minimizes the possibility of false detection in an environment where false alarms may occur due to pattern distortion among elements of an array antenna. The pattern distortion weakens the GPS signal strength at low elevation. It becomes confusing to detect a spoofing signal based on the relative power difference between GPS L1 and L2, especially when GPS L2 has weak signal strength. We propose design parameters for the relative power threshold including beamforming gain, the minimum received power difference between L1 and L2, and the patch antenna gain difference between L1 and L2. In addition, in order to eliminate the weak signal strength of GPS L2 in the spoofing detection process, we propose a rotation matrix that sets the elevation mask based on platform coordinates. Array antennas generally do not have high usefulness in commercial areas where receivers are operated alone, but are considered essential in military areas where GPS receivers are used together with signal processing for beamforming in the direction of GPS satellites. Through laboratory and live sky tests using the device under test, the proposed scheme with an elevation mask detects spoofing signals well and reduces the probability of false detection relative to that without the elevation mask.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.283-289
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• 2015

In this paper, a GNSS interference detection algorithm based on an adaptive fading Kalman filter is proposed to detect a spoofing signal which is one of the threatening GNSS intentional interferences. To detect and mitigate the spoofing signal, the fading factor of the filter is used as a detection parameter. For simulation, the effect of the spoofing signal is modeled by the ramp type bias error of the pseudorange to emulate a smart spoofer and the change of the fading factor value according to ramp type bias error is quantitatively analyzed. In addition, the detection threshold is established to detect the spoofing signal by analyzing the change of the error covariance and the effect of spoofing is mitigated by controlling the Kalman gain of the filter. To verify the performance analysis of the proposed algorithm, various simulations are implemented. Through the results of simulations, we confirmed that the proposed algorithm works well.

• Journal of KIISE
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• v.42 no.4
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• pp.483-486
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• 2015

Security systems that use face recognition are vulnerable to spoofing attacks where unauthorized individuals use a photo or video of authorized users. In this work, we propose a method to detect a face spoofing attack with a video of an authorized person. The proposed method uses three sequential frames in the video to extract features by using Fourier Transform and Dense-SIFT filter. Then, classification is completed with a Support Vector Machine (SVM). Experimental results with a database of 200 valid and 200 spoof video clips showed 99% detection accuracy. The proposed method uses simplified features that require fewer memory and computational overhead while showing a high spoofing detection accuracy.

• Journal of Internet Computing and Services
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• v.9 no.4
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• pp.85-96
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• 2008

An authentication procedure on wired and wireless network will be done based on the registration and management process storing both the user's IP address and client device's MAC address information. However, existent MAC address registration/administration mechanisms were weak in MAC Spoofing attack as the attacker can change his/her own MAC address to client's MAC address. Therefore, an advanced mechanism should be proposed to protect the MAC address spoofing attack. But, existing techniques sequentially compare a sequence number on packet with previous one to distinguish the alteration and modification of MAC address. However, they are not sufficient to actively detect and protect the wireless MAC spoofing attack. In this paper, both AirSensor and AP are used in wireless network for collecting the MAC address on wireless packets. And then proposed module is used for detecting and protecting MAC spoofing attack in real time based on MAC Address Lookup table. The proposed mechanism provides enhanced detection/protection performance and it also provides a real time correspondence mechanism on wireless MAC spoofing attack with minimum delay.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.187-194
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• 2021

This paper presents a margin-based face liveness detection method with behavioral confirmation to prevent spoofing attacks using deep learning techniques. The proposed method provides a possibility to prevent biometric person authentication systems from replay and printed spoofing attacks. For this work, a set of real face images and fake face images was collected and a face liveness detection model is trained on the constructed dataset. Traditional face liveness detection methods exploit the face image covering only the face regions of the human head image. However, outside of this region of interest (ROI) might include useful features such as phone edges and fingers. The proposed face liveness detection method was experimentally tested on the author's own dataset. Collected databases are trained and experimental results show that the trained model distinguishes real face images and fake images correctly.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.9
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• pp.1273-1280
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• 2014

This paper considers a GPS anti-spoofing problem. Spoofing is an intentional interference that mislead the GNSS receiver. The spoofing attack is very significant since the target receiver is not aware of being attacked from spoofing. Accelerometers can be used to detect the spoofing signal by being compared with the acceleration obtained from GPS information using Kalman filter. In this paper we propose an N by N-point average and M-point window algorithm to detect GPS spoofing by using accelerometers and GPS outputs. The performance of the proposed algorithm is analyzed using actual vehicle trajectory and spoofing trajectory generated from INS and GPS toolbox for simulation.