A common, geometry-preserving GNSS shift is invisible to distance-only swarm defenses, but a small set of trusted anchors can restore absolute positions, and a derived detection floor predicts how fast a covert ramp must be to be caught.
Black-box Stealthy GPS Attacks on Unmanned Aerial Vehicles
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abstract
This work focuses on analyzing the vulnerability of unmanned aerial vehicles (UAVs) to stealthy black-box false data injection attacks on GPS measurements. We assume that the quadcopter is equipped with IMU and GPS sensors, and an arbitrary sensor fusion and controller are used to estimate and regulate the system's states, respectively. We consider the notion of stealthiness in the most general form, where the attack is defined to be stealthy if it cannot be detected by any existing anomaly detector. Then, we show that if the closed-loop control system is incrementally exponentially stable, the attacker can cause arbitrarily large deviation in the position trajectory by compromising only the GPS measurements. We also show that to conduct such stealthy impactfull attack values, the attacker does not need to have access to the model of the system. Finally, we illustrate our results in a UAV case study.
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Rigid-Covert GNSS Spoofing of UAV Swarms: A Structural Blind Spot, Its Detection Limit, and Absolute-Anchor Defenses
A common, geometry-preserving GNSS shift is invisible to distance-only swarm defenses, but a small set of trusted anchors can restore absolute positions, and a derived detection floor predicts how fast a covert ramp must be to be caught.