Context-Aware GNSS API Security for DoS-Resilient Positioning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing wireless communication systems, particularly 5G NR, lack efficient methods to enhance GNSS positioning by securing the GNSS API and handling denial-of-service events without additional hardware or computational resources.
Innovation Solution
A context-aware secure GNSS API is developed using GNSS, WWAN, and sensor measurements, along with a look-ahead context based on map-aiding and predicted trajectory, to dynamically determine robustness levels for API requests and rejections, enhancing GNSS positioning performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If additional hardware or computational resources are allocated to enhance GNSS positioning and detect denial-of-service events, then positioning performance and security are improved, but device complexity and cost increase
Solution Approach 1:
The system uses existing sensor measurements (accelerometer, gyroscope, magnetometer) and WWAN measurements that are already being collected by the device for other purposes. These existing resources are repurposed to detect denial-of-service events and enhance GNSS positioning, eliminating the need for additional dedicated hardware while improving positioning reliability
Solution Approach 2:
The patent makes existing components serve multiple functions: sensor measurements originally intended for motion detection are now also used for detecting API injection attempts and enhancing GNSS positioning accuracy. The same processor that handles normal device operations now also performs security verification and positioning enhancement, reducing the need for specialized hardware
2Reliability
If the system implements comprehensive security checks for GNSS API requests using context analysis, then security against denial-of-service events is improved, but processing time and computational overhead increase
Solution Approach 1:
The system continuously monitors and analyzes sensor measurements and device context in the background before GNSS API requests are made. By pre-establishing baseline behavior patterns and continuously updating context information, the system can quickly verify incoming API requests without performing comprehensive analysis at the time of each request, thus reducing processing time while maintaining security
Solution Approach 2:
The system uses feedback from sensor measurements and device state to dynamically adjust security verification. By continuously monitoring device context and comparing it against expected patterns, the system can quickly identify anomalies indicating denial-of-service events without requiring time-consuming analysis of each individual API request
3Measurement precision
If the system dynamically adjusts operating modes based on environment and predicted receiver state, then GNSS positioning accuracy is improved, but system complexity increases
Solution Approach 1:
The system dynamically adjusts GNSS receiver operating modes based on real-time sensor measurements and predicted device state. By continuously monitoring device orientation, motion state, and environmental context, the system adapts positioning strategies to current conditions, improving accuracy without requiring complex manual configuration or multiple specialized systems
4Measurement precision
If the system uses multiple measurement sources (GNSS, WWAN, sensors) for context identification, then detection accuracy for denial-of-service events is improved, but computational resources required increase
Solution Approach 1:
The patent combines sensor measurements, WWAN measurements, and GNSS data into a unified context model. By integrating these diverse data sources and analyzing them collectively to identify device state and detect anomalies, the system achieves high detection accuracy while avoiding the need for separate processing pipelines for each measurement type, thus reducing overall computational overhead
Data Source
AI summary
Aspects presented herein may enable a UE to secure global navigation satellite system (GNSS) application programming interface (API) based on context information. In one aspect, a UE receives, from at least one API, a request or an injection for an operating mode of the UE. The UE identifies an environment of the UE for the request or the injection based on at least one of: a set of GNSS measurements, a set of WWAN measurements, or a set of sensor measurements. The UE identifies, based on the request or the injection, a current receiver state and a predicted receiver state of the UE based on at least one of: location information, a position trajectory, map data, or traffic information. The UE configures the operating mode of the UE based on the environment, the current receiver state, and the predicted receiver state.