GPS Timing Anomaly Detection Using an Independent Clock
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Solution Overview
Problem
Digital systems are vulnerable to timing anomalies, particularly from GPS spoofing attacks, which can compromise critical infrastructure by providing misleading timing and positioning data.
Innovation Solution
A timing anomaly detection system using an independent clock source, such as a cesium clock, and a GPS receiver, where a frequency multiplier and timing error measuring unit analyze the timing signals to detect discrepancies and generate alerts when deviations exceed a configurable threshold, indicating a potential spoofing attack.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If GPS signals are used for timing in digital systems, then positioning and timing functionality is provided, but the system becomes vulnerable to spoofing attacks that can compromise timing integrity
Solution Approach 1:
The patent introduces an intermediary timing anomaly detection system that sits between the GPS receiver and the digital system. This intermediary monitors GPS timing signals for anomalies using statistical analysis and machine learning algorithms, blocking compromised signals before they can affect the digital system while allowing legitimate GPS timing functionality to operate.
Solution Approach 2:
The patent implements feedback mechanisms where the timing anomaly detection system continuously monitors GPS signals, compares them against expected patterns and multiple reference sources, and provides real-time alerts when anomalies are detected. This feedback loop enables the system to adapt to changing conditions and maintain timing integrity despite GPS vulnerabilities.
2Reliability
If GPS spoofing protection is implemented, then timing integrity is improved, but system complexity increases due to additional detection mechanisms
Solution Approach 1:
The patent segments the timing anomaly detection function into modular components: signal acquisition modules, processing modules that apply statistical tests, machine learning analysis modules, and decision-making modules. This segmentation allows each component to be optimized independently and facilitates easier implementation and maintenance while maintaining comprehensive spoofing protection.
Solution Approach 2:
The patent designs the timing anomaly detection system to perform multiple functions: detecting GPS spoofing, validating timing signals, providing alerts, and potentially switching to alternative timing sources. This multi-functionality reduces overall system complexity by consolidating multiple security and timing functions into a single integrated system rather than requiring separate systems for each function.
3Reliability
If real-time GPS spoofing detection is implemented, then protection against spoofing attacks is provided, but processing time and computational resources increase
Solution Approach 1:
The patent implements periodic action by using discrete statistical tests at specific intervals rather than continuous analysis. The system performs statistical anomaly detection at defined sampling rates and uses periodic correlation tests against known GPS signal structures. This approach provides real-time protection while limiting processing time to discrete intervals, reducing overall computational burden compared to continuous analysis.
Solution Approach 2:
The patent applies preliminary action by pre-computing statistical thresholds, training machine learning models offline, and preparing reference signal patterns before actual GPS signal analysis. This preliminary preparation reduces the computational complexity during real-time operation, allowing rapid anomaly detection without excessive processing time during critical spoofing detection events.
Data Source
AI summary
Disclosed herein are system, method, and computer program product embodiments for adapting to malware activity on a compromised computer system by detecting timing anomalies between timing signals. An embodiment operates by analyzing first timing data accessed from a validated source and second timing data accessed from an unvalidated receiver source in order to compute a threat detection value, which is utilized to determine if there is a discrepancy or anomaly in the timing or frequency of either the validated and unvalidated sources.