AI-based GNSS Spoofing and GPS Interference Detection in Aviation

Sam Suseelan

doi:10.36948/ijfmr.2024.v06i01.79099

AI-based GNSS Spoofing and GPS Interference Detection in Aviation

Author(s)	Mr. Sam Suseelan
Country	India
Abstract	Global Navigation Satellite Systems (GNSS) are now crucial to modern aviation navigation systems for positioning, routing and operation monitoring. However, the GNSS technology is subject to spoofing and interference attacks that could compromise the accuracy of navigation and consequently affect aviation safety. Aviation cybersecurity systems need to become more adaptive and intelligent to detect signal manipulation incidents as they become more common. The focus of this study was to explore the application of Artificial Intelligence (AI) based techniques in the detection of GNSS spoofing and GPS interference in aviation applications. An experimental approach based on simulations was employed, where the GNSS signal datasets were generated under normal and manipulated signal conditions. During the classification process, signal characteristics (signal strength variation, positioning deviation, timing variation, and signal-to-noise ratio anomalies) were examined. A machine learning model based on the random forest algorithm was developed to identify legitimate, spoofed, and interfered navigation signals The experimental results showed that the presented strategy was able to maintain stable classification performance under simulated attacks. The model had good accuracy, precision, recall, and F1 score, showing its efficacy in detecting abnormal GNSS signal behavior in the experimental environment. It was also found that the spoofed signals caused measurable instabilities in positioning stability and positioning synchronization patterns, which were correctly recognized by the AI classifier. The study proposes that machine learning can be used as an aid to create more adaptive GNSS security solutions for aviation navigation systems. The results of the experiments demonstrate that the presented AI-assisted anomaly detection methods could be valuable to enhance aviation cyber security and navigation resilience in the real world. To evaluate the effectiveness of AI-based GNSS protection frameworks, further studies with real-world aviation data and operational testing environments are recommended for the future.
Keywords	Keywords: GNSS Spoofing, GPS Interference, Aviation Cybersecurity, Artificial Intelligence, Machine Learning, Navigation Security, Anomaly Detection
Field	Engineering
Published In	Volume 6, Issue 1, January-February 2024
Published On	2024-01-05
DOI	https://doi.org/10.36948/ijfmr.2024.v06i01.79099

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AI-based GNSS Spoofing and GPS Interference Detection in Aviation

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