A Framework for GNSS Spoofing Detection Through Combinations of Metrics
Fabian Rothmaier, Yu‐Hsuan Chen, Sherman Lo, Todd Walter
Abstract
We present a framework for GNSS spoofing detection combining an arbitrary number of metrics while guaranteeing a fixed maximum false alert probability. The detection test assumes a simple form that makes it suitable for real time applications. We define criteria for metrics to be used within this framework and demonstrate compatibility with a range of commonly used metrics. We achieve a more than 70% reduction in worst-case missed detection probability compared to conventional metric combination techniques.
Topics & Concepts
GNSS applicationsSpoofing attackComputer scienceMetric (unit)Data miningReal-time computingAlgorithmGlobal Positioning SystemEngineeringComputer securityTelecommunicationsOperations managementGNSS positioning and interferenceIndoor and Outdoor Localization TechnologiesBluetooth and Wireless Communication Technologies