Abstract
Due to the low received power of Global Navigation Satellite Signals (GNSS), the performance of GNSS receivers can be disrupted by anthropogenic radio frequency interferences, with intentional jamming and spoofing activities being among the most critical threats. It is reported in the literature that modern, GNSS-equipped Android smartphones are generally resistant to simplistic spoofing, and many recent contributions support such a biased belief. In this paper, we present the results of a test campaign designed to further stress the resilience of such devices to simplistic spoofing attacks and highlight their actual vulnerability. We then propose an effective spoofing detection technique, that exploits the spatial and temporal correlation of the counterfeit signals by leveraging the statistical analysis of raw GNSS measurements. By not requiring access to the low signal processing level of the GNSS id=Greceiverprocessor, the proposed solution applies to id=Gany id=Gdevicedevices embedding a GNSS id=Greceiver that providesunit and providing output raw GNSS measurements, such as current Android smartphones. Vulnerability analysis and validation of the proposed technique were conducted in a controlled environment by transmitting realistic, id=Gcounterfeitfake Global Positioning System id=R1(GPS) L1/CA navigation signals to a variety of Android smartphones id=Gembedding also differentand embedded GNSS chipsets. id=GIn the process, id=GWWe show that, under proper conditions, the devices were vulnerable to the attacks and that the effects were visible through their raw measurements, i.e., Carrier-to-noise ratio (C/N0), pseudo-range measurements, and position estimates. In particular, the study demonstrates that cross-correlation between id=Gthe C/N0 time series provided by each device id=Gforabout different GNSS satellites id=Gincreasesincrease under spoofing conditions, thus constituting id=Gan effectivea proper metric to detect the attack within a few seconds.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
