Improving GNSS spoofing awareness in smartphones via statistical processing of raw measurements

Due to the low received power of Global Navigation Satellite Signals (GNSS), performance GNSS receivers can be disrupted by anthropogenic radio frequency interferences, with intentional jamming and spoofing activities being among most critical threats. It is reported in literature that modern, GNSS-equipped Android smartphones are generally resistant simplistic spoofing, many recent contributions support such a biased belief. In this paper, we present results test campaign designed further stress resilience devices attacks highlight their actual vulnerability. We then propose an effective detection technique, exploits spatial temporal correlation counterfeit signals leveraging statistical analysis raw measurements. By not requiring access signal processing level id=Greceiverprocessor, proposed solution applies id=Gany id=Gdevicedevices embedding id=Greceiver providesunit providing output measurements, as current smartphones. Vulnerability validation technique were conducted controlled environment transmitting realistic, id=Gcounterfeitfake Positioning System id=R1(GPS) L1/CA navigation variety id=Gembedding also differentand embedded chipsets. id=GIn process, id=GWWe show that, under proper conditions, vulnerable effects visible through i.e., Carrier-to-noise ratio (C/N0), pseudo-range position estimates. particular, study demonstrates cross-correlation between id=Gthe C/N0 time series provided each device id=Gforabout different satellites id=Gincreasesincrease thus constituting id=Gan effectivea metric detect attack within few seconds.