METHODS FOR DETECTING SPOOFING IN MARITIME NAVIGATION SYSTEMS

Abstract

The article is devoted to the systematization and comprehensive comparative analysis of modern methods for detecting GPS/GNSS spoofing in maritime navigation systems. Particular attention is paid to the growing relevance of this issue in the context of increasing dependence on satellite navigation and the associated risks to the safety and reliability of maritime operations. The physical principles underlying spoofing attacks are examined in detail, including signal generation, synchronization, and manipulation mechanisms, as well as their classification according to the level of technical sophistication, target objects (shipborne receivers, navigation subsystems), and potential consequences for maritime safety, such as route distortion, collision risks, and loss of situational awareness.

The study provides an in-depth analysis of detection methods based on several complementary approaches. These include monitoring of signal parameters, in particular signal strength and carrier-to-noise density ratio (C/N₀), which allows identification of abnormal signal behavior; consistency checks of inter-satellite Doppler shifts to detect inconsistencies in satellite motion patterns; and cross-verification with alternative positioning, navigation, and timing (PNT) sources, such as AIS, eLoran, and other independent systems, ensuring redundancy and reliability. Special emphasis is placed on hybrid inertial-satellite navigation systems that employ Kalman filtering to integrate data from multiple sensors and enhance robustness against spoofing.

In addition, the article explores advanced data-driven techniques, including machine learning methods for anomaly detection. Specifically, the application of recurrent neural networks (LSTM) for temporal pattern recognition and ensemble classifiers for improving detection accuracy and reducing false positives is discussed. The advantages and limitations of each method are critically evaluated in terms of implementation complexity, computational requirements, and effectiveness under real-world conditions.

Based on the conducted analysis, a multi-layered architecture for protecting maritime navigation systems is proposed. This architecture integrates signal-level, navigation-level, and network-level detection mechanisms into a unified framework, providing a comprehensive and adaptive defense against spoofing attacks. The technical prerequisites for its effective implementation are also defined, including requirements for sensor integration, data synchronization, and system interoperability.