• Journal of Positioning, Navigation, and Timing
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• 제7권3호
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• pp.127-138
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• 2018

Spoofing attacks including meaconing can provide a bogus position to a victim GPS receiver, and those attacks are notably difficult to detect at the point of view on the receiver. Several countermeasure techniques have been studied to detect, classify, and cancel the spoofing signals. Based on the countermeasure techniques, we have developed an anti-spoofing equipment that detects and mitigates or eliminates the spoofing signal based on raw measurements. Although many anti-spoofing techniques have been studied in the literatures, the evaluation test system is not deeply studied to evaluate the anti-spoofing equipment, which includes detection, mitigation, and elimination of spoofing signals. Each study only has a specific test method to verify its anti-spoofing technique. In this paper, we propose the performance evaluation test system that includes both spoofing signal injection system and its injection scenario with the constraints of stand-alone anti-spoofing techniques. The spoofing signal injection scenario is designed to drive a victim GPS receiver that moves to a designed position, where the mitigation and elimination based anti-spoofing algorithms can be successively evaluated. We evaluate the developed anti-spoofing equipment and a commercial GPS receiver using our proposed performance evaluation test system. Although the commercial one is affected by the test system and moves to the designed position, the anti-spoofing equipment mitigates and eliminates the injected spoofing signals as planned. We evaluate the performance of anti-spoofing equipment on the position error of the circular error probability, while injecting spoofing signals.

• Journal of Positioning, Navigation, and Timing
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• 제5권4호
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• pp.165-172
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• 2016

A Global Navigation Satellite System (GNSS), which is typically exemplified by the Global Positioning System (GPS), employs a open signal structure so it is vulnerable to spoofing electronic attack using a similar malicious signal with that used in the GPS. It is necessary to require a spoofing test evaluation environment to check the risk of spoofing attack and evaluate the performance of a newly developed anti-spoofing technique against spoofing attacks. The present paper proposed a simulation method of spoofing environment based on simulator that can be implementable in a test room and analyzed the spoofing simulation performance using commercial GPS receivers. The implemented spoofing simulation system ran synchronized two GPS simulator modules in a single scenario to generate both of spoofing and GPS signals simultaneously. Because the signals are generated in radio frequency, a commercial GPS receiver can be tested using this system. Experimental test shows the availability of this system, and anti-spoofing performance of a commercial GPS receiver has been analyzed.

• 한국군사과학기술학회지
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• 제13권2호
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• pp.296-303
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• 2010

The term "spoofing" refers to the transmission of counterfeit signals to provide undetectable falsification of GPS service. A spoofing can be accomplished using information from open literature which defines the signal format and the data structure. Spoofing is intended either to produce erroneous navigation solutions or saturate the processor of the victim receiver. The GPS receiver has no way to get rid of the effect of a spoofing because GPS receivers for civil service do not have an anti-spoofing scheme. This paper analyzes the spoofing characteristics, spoofing methods and environment conditions. And the spoofing effects on GPS receiver are analyzed in detail using the designed software-based spoofer and the Nordnav receiver.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권9호
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• pp.2424-2441
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• 2012

In this paper, we propose a fake iris detection method that combines the optical and textural features of the human eye. To extract the optical features, we used dual Purkinje images that were generated on the anterior cornea and the posterior lens surfaces based on an analytic model of the human eye's optical structure. To extract the textural features, we measured the amount of change in a given iris pattern (based on wavelet decomposition) with regard to the direction of illumination. This method performs the following two procedures over previous researches. First, in order to obtain the optical and textural features simultaneously, we used five illuminators. Second, in order to improve fake iris detection performance, we used a SVM (Support Vector Machine) to combine the optical and textural features. Through combining the features, problems of single feature based previous works could be solved. Experimental results showed that the EER (Equal Error Rate) was 0.133%.