Spoofing is a kind of deliberate interference that aims to manipulate global navigation satellite system (GNSS) receivers into counterfeit position solutions. Conventional anti-spoofing methods are implemented prior to the calculation of the position solution, depending on the specific spoofing attack mechanisms. The paper presents a spoofing detection and mitigation method implemented in the position domain. The proposed method projects the correlograms of the visible satellites to a position-clock bias domain to construct the position domain projected correlogram. P(Y) code signatures retrieved from a reference station receiver are used to identify the counterfeit position solution and remove it from the victim receiver. Compared with the conventional single-channel spoofing detection technique, the proposed anti-spoofing method is more robust against thermal noise by combining the energy from multiple satellites. Detailed mathematical derivation of the statistical characteristics of this method is presented. Its effectiveness is validated using a realistic dataset generated by a Spirent GNSS simulator and NordNav wideband front-end. Results show that the proposed algorithm is capable of not only detecting a spoofing attack but also removing the spoofing effect from the victim receiver.

A spoofing attack on a global navigation satellite system (GNSS) receiver is a threat to a significant community of GNSS users due to the high stakes involved. This paper investigates the use of slope based metrics for the detection of spoofing. The formulation of slope based metrics involves monitoring correlators along with tracking correlators in the receiver's channel, which are slaved to the prompt tracking correlator. In this study, using some candidate metrics, detectors have been formed through the analysis of simulated spoofing attacks. A theoretical variance of each metric has also been calculated as a reference for the threshold. A threshold is estimated using the measured variance from the clean signals, for specific false alarm rate. By using the measured threshold, detectors are formed based on slope metrics. These detectors have been tested using TEXBAT data. The results show that the differential slope metrics have good performance. The results have also been compared with some other techniques of spoofing detection.

Nowadays, the security of ASV systems is increasingly gaining attention. As one of the common spoofing methods, replay attacks are easy to implement but difficult to detect. Many researchers focus on designing various features to detect the distortion of replay attack attempts. Constant-Q cepstral coefficients (CQCC), based on the magnitude of the constant-Q transform (CQT), is one of the striking features in the field of replay detection. However, it ignores phase information, which may also be distorted in the replay processes. In this work, we propose a CQT-based modified group delay feature (CQTMGD) which can capture the phase information of CQT. Furthermore, a multi-branch residual convolution network, ResNeWt, is proposed to distinguish replay attacks from bonafide attempts. We evaluated our proposal in the ASVspoof 2019 physical access dataset. Results show that CQTMGD outperformed the traditional MGD feature, and the fusion with other magnitude-based and phase-based features achieved a further improvement. Our best fusion system achieved 0.0096 min-tDCF and 0.39% EER on the evaluation set and it outperformed all the other state-of-the-art methods in the ASVspoof 2019 physical access challenge.

Global Navigation Satellite System (GNSS) safety issues of have been of concern for some time. Spoofing attacks have received much attention as they can be difficult to detect and have the potential to cause disruption at best and major damage in extremis. To mitigate such threats, a spoofing detection method based on the consistency check of Doppler positioning fixes and pseudorange positioning fixes is proposed. The primary contributions of this paper include establishing a Generalised Likelihood Ratio Test (GLRT)-based statistical detection model for the introduced spoofing detection method and efficiently improving the accuracy of the Doppler positioning method as well as the performance of the detection approach by a modified α-filter-based Doppler smoothing technique. Theoretical performance of the proposed detection model is analysed. Monte Carlo simulations were also conducted to verify the theoretical analysis. Moreover, grounded on the developed test statistic and the optimised threshold, a consistency check module was specifically realised in both software defined and real-time GNSS receivers. Additionally, a Doppler smoothing technique was applied to the receivers. Spoofing attack experiments on both software defined and real-time platforms validated the effectiveness of the statistical spoofing detection model.

The Global Positioning System (GPS) has become widespread in many civilian applications. GPS signals are vulnerable to interference and even low-power interference can easily spoof GPS receivers. In this paper, two techniques are proposed based on correlators and adaptive filtering to diminish the effect of spoofing on GPS-based positioning. The suggested algorithms are implemented in the tracking loop of the receiver. As a first method, a high-resolution correlator is utilised to avoid big parts of the influence of interference. To improve the results, a multicorrelator technique is also employed. In the second method, an adaptive filter is used for estimating the parameters of authentic plus spoof signals. Interference elimination is performed by subtracting the estimated conflict effects from the measured correlation function. These techniques provide easy-to-implement quality assurance tools for anti-spoofing. As a primary step, in this article, the proposed algorithms have been implemented in a Software Receiver (SR) to prove the concept of idea in multipath-free environments.

A speaker verification system automatically accepts or rejects a claimed identity of a speaker based on a speech sample. Recently, a major progress was made in speaker verification which leads to mass market adoption, such as in smartphone and in online commerce for user authentication. A major concern when deploying speaker verification technology is whether a system is robust against spoofing attacks. Speaker verification studies provided us a good insight into speaker characterization, which has contributed to the progress of voice conversion technology. Unfortunately, voice conversion has become one of the most easily accessible techniques to carry out spoofing attacks; therefore, presents a threat to speaker verification systems. In this paper, we will briefly introduce the fundamentals of voice conversion and speaker verification technologies. We then give an overview of recent spoofing attack studies under different conditions with a focus on voice conversion spoofing attack. We will also discuss anti-spoofing attack measures for speaker verification.