Ali Jafarnia-Jahromi

GPS Vulnerability to Spoofing Threats and a Review of Antispoofing Techniques

Article deposited according to Hindawi Publishing Corporation policy for the International Journal of Navigation and Observation: http://www.hindawi.com/journals/ijno/guidelines/, August 22, 2012.

GNSS spoofing detection in handheld receivers based on signal spatial correlation

Spoofing and jamming in the form of transmitting counterfeit location information and denying services are an emerging threat to GNSS receivers. In general, spoofing is a deliberate attack that aims to coerce GNSS receivers into generating false navigation solutions. The spoofing attack is potentially more hazardous than jamming since the target receiver is not aware of this threat and it is still providing position/navigation solutions which seem to be reliable. One major limitation of spoofers is that they are required to transmit several highly correlated GNSS signals simultaneously often from a single source in order to present a truthful navigation solution to the receiver. Different GNSS signals sourced from a single transmitter have essentially the same spatial signature, which as shown in this paper, can be utilized to discriminate the spoofing signals. In this paper a moving antenna is investigated to discriminate between the spatial signatures of the authentic and the spoofing signals based on monitoring the amplitude and Doppler correlation of the visible satellite signals. The effectiveness of this detection method is studied and verified based on a set of experiments.

Spoofing detection, classification and cancelation (SDCC) receiver architecture for a moving GNSS receiver

Abstract Spoofing in the form of transmitting fake GNSS signals is a deliberate attack that aims to mislead GNSS receivers into generating false position/time solutions. Current work on GNSS spoofing has mainly focused on spoofing detection where the proposed algorithms only indicate the presence of spoofing attacks. A new architecture consisting of spoofing detection, authentic/spoofing signal classification and spoofing cancelation known as spoofing detection, classification and cancelation for moving GNSS receivers is proposed. Predespreading and acquisition level analysis are performed to detect the presence of spoofing interference. The receiver motion is then used to classify the signals tracked into two groups, namely spoofing and authentic signal sets. A successive spoofing cancelation method is then developed to remove the spoofing signals from the raw digitized samples. It is shown that canceling out the spoofing signals removes multiple access interference and significantly improves the authentic signals’ detectability and tracking performance. Finally, after spoofing cancelation, authentic signals are acquired and tracked and their corresponding measurements are passed to a PVT engine for a reliable position solution. The proposed receiver architecture is analyzed in the acquisition, tracking and positioning layers.

Overview of Spatial Processing Approaches for GNSS Structural Interference Detection and Mitigation

GNSS-dependent positioning, navigation, and timing synchronization procedures have a significant impact on everyday life. Thus, such an extensively used system progressively become an attractive target for illegal exploitation and attacks. Position and timing solutions provided by GNSS receivers can be threatened by structural interference such as spoofing threats. This paper provides an overview of recent research work on GNSS signal authentication utilizing spatial processing methods. Different spatial processing approaches for spoofing detection, classification and mitigation are characterized and compared. Three different processing methods, namely antenna array processing, moving receiver and cloud based spoofing countermeasure are analyzed in details. The benefits and disadvantages of each are discussed.

A GNSS structural interference mitigation technique using antenna array processing

Position solutions provided by Global Navigation Satellite Systems (GNSS) can be completely misled by structural interference or spoofing threats. An approach utilizing an antenna array is proposed in order to suppress spoofing attacks. The proposed method is based on the assumption that all spoofing signals are transmitted from a single point source. A spatial domain processing technique is proposed to extract the spoofing signal steering vector and consequently to discard the spoofing signals. This method is implemented before despreading and acquisition stage of a GNSS receiver. Hence, it does not impose a heavy computational load on the receiver operational process since it does not require any extensive search in the code and Doppler domains to separately despread individual authentic and spoofing signals. Moreover, the proposed method does not require any antenna array calibration process. This pre-despreading interference mitigation technique is further extended to maximize signal-to-noise ratio (SNR) of each individual authentic GNSS signal. Simulation results show that the proposed method effectively countermeasures spoofing attacks for a wide range of received spoofing power.

An approach to discriminate GNSS spoofing from multipath fading

GNSS signals are vulnerable to various types of interference including jamming and spoofing attacks. Spoofing signals are designed to deceive target GNSS receivers without being detected by conventional receiver quality monitoring metrics. This paper focuses on detecting an overlapped spoofing attack where the correlation peaks of the authentic and spoofing signals interact during the attack. Several spoofing detection and signal quality monitoring (SQM) metrics are introduced. This paper proposes a spoofing detection architecture utilizing combination of different metrics to detect spoofing signals and distinguish them from multipath signals. Experimental results show that the pre-despreading spoofing detection metrics such as variance analysis are not sensitive to multipath propagation and can be used in conjunction with post-despreading methods to correctly detect spoofing signals. Several test scenarios based on different spoofing and multipath cases are performed to demonstrate the effectiveness of the proposed architecture to correctly detect spoofing attack ands distinguish them from multipath.