Real-Time GPS Spoofing Detection via Correlation of Encrypted Signals

O’Hanlon, Brady W.; Psiaki, Mark L.; Bhatti, Jahshan A.; Shepard, Daniel P.; Humphreys, Todd E.

doi:10.1002/navi.44

Cited by 90 publications

(51 citation statements)

References 8 publications

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“…That is, knowledge of the local receiver positions can be quite useful if the platform rotation is known too, for example, by the use of gyros and accelerometers. The proposed GLRT detectors (10) and (12), and the mean distance detector (13) performs quite well, despite not having any knowledge of the true receiver positions. The proposed singular value detec tor (14) shows quite poor performance, and is also computationally more burdensome than the other detectors.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…These issues were highlighted in the so called Volpe report [1] in 2001, and much effort has been put in the research on spoofing [2][3][4] and anti spoofing techniques [5][6][7][8][9][10][11][12][13][14][15][16] in the last decade. The recent achieve ments on GPS spoofing techniques [2][3][4] have further raised these issues, and shown that it is a real threat.…”

Section: Introductionmentioning

confidence: 99%

“…Several spoofing detectors have been proposed based on cross checks with other sensors, for example intertial measurement units (lMU) [2] or cross-correlation with a secure GNSS receiver [9,10,17]. Other techniques have been proposed based on the detection of different types of anomalies in the correlator outputs caused by spoofing [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

GNSS spoofing detection using multiple mobile COTS receivers

Axell

Larsson

Persson

2015

2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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In this paper we deal with spoofing detection in GNSS receivers. We derive the optimal genie detector when the true positions are per fectly known, and the observation errors are Gaussian, as a bench mark for other detectors. The system model considers three dimen sional positions, and includes correlated errors. In addition, we pro pose several detectors that do not need any position knowledge, that outperform recently proposed detectors in many interesting cases.

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Section: Numerical Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

GNSS spoofing detection using multiple mobile COTS receivers

Axell

Larsson

Persson

2015

2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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show abstract

“…Currently, numerous institutions have conducted thorough studies of this anti-spoofing technology [10,11]. A disadvantage of this method is that the signal architecture of a navigation system must be changed, which requires design changes for satellite transmitters and ground receivers.…”

Section: Signal Encryptionmentioning

confidence: 99%

Calculation of the lower limit of the spoofing-signal ratio for a GNSS receiver-spoofer

Zhou

2018

J Wireless Com Network

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A receiver-spoofer is one of the most covert global navigation satellite system (GNSS) spoofing attacks and can only be effectively detected by the combination of multiple anti-spoofing technologies. In this paper, an analysis of influencing parameters for receiver-spoofers indicates that the ratio of the spoofing signal amplitude versus the authentic signal amplitude (spoofing-signal ratio) is a key parameter for spoofing results. For a spoofer to ensure covertness, the goal is to maintain a low spoofing-signal ratio. The carrier phase difference and code phase difference between authentic signals and spoofing signals resulted in errors in the position estimation of the target receiver increase the lower limit of the spoofing-signal ratio required for successful spoofing. A spoofing signal alters the phase of local replicate code based on the original balance of a receiver phase discriminator to seize control. Based on this principle, the lower limit of the spoofing-signal ratio that corresponds to various phase discriminator spacings, carrier phase differences, and code phase differences is deduced in this paper. Two tests are designed for the simulation source and authentic navigation signals to verify the deduced formula. The lower limit of the spoofing-signal ratio obtained from these tests matches the calculated results, which proves the validity and effectiveness of the derived algorithm.

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“…Iranians used the "spoofing" technique which considers landing altitudes, longitudinal and latitudinal data accurately causing the drone to land to the wanted location, without needing to crack the remote-control signal and communications from the control center [27].…”

Section: Iran Hijacking Of Us Dronementioning

confidence: 99%

Cyber-Security Incidents: A Review Cases in Cyber-Physical Systems

Al-Mhiqani¹,

Ahmad²,

Yassin³

et al. 2018

ijacsa

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Abstract-Cyber-Physical Systems refer to systems that have an interaction between computers, communication channels and physical devices to solve a real-world problem. Towards industry 4.0 revolution, Cyber-Physical Systems currently become one of the main targets of hackers and any damage to them lead to high losses to a nation. According to valid resources, several cases reported involved security breaches on Cyber-Physical Systems. Understanding fundamental and theoretical concept of security in the digital world was discussed worldwide. Yet, security cases in regard to the cyber-physical system are still remaining less explored. In addition, limited tools were introduced to overcome security problems in Cyber-Physical System. To improve understanding and introduce a lot more security solutions for the cyber-physical system, the study on this matter is highly on demand. In this paper, we investigate the current threats on Cyber-Physical Systems and propose a classification and matrix for these threats, and conduct a simple statistical analysis of the collected data using a quantitative approach. We confirmed four components i.e., (the type of attack, impact, intention and incident categories) main contributor to threat taxonomy of Cyber-Physical Systems.

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Real-Time GPS Spoofing Detection via Correlation of Encrypted Signals

Cited by 90 publications

References 8 publications

GNSS spoofing detection using multiple mobile COTS receivers

GNSS spoofing detection using multiple mobile COTS receivers

Calculation of the lower limit of the spoofing-signal ratio for a GNSS receiver-spoofer

Cyber-Security Incidents: A Review Cases in Cyber-Physical Systems

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