Impact of Dataset and Model Parameters on Machine Learning Performance for the Detection of GPS Spoofing Attacks on Unmanned Aerial Vehicles

Impact of Dataset and Model Parameters on Machine Learning Performance for the Detection of GPS Spoofing Attacks on Unmanned Aerial Vehicles

GPS spoofing attacks are a severe threat to unmanned aerial vehicles. These attacks manipulate the true state of the unmanned aerial vehicles, potentially misleading the system without raising alarms. Several techniques, including machine learning, have been proposed to detect these attacks. Most of...

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Bibliographic Details
Main Authors: Tala Talaei Khoei, Shereen Ismail, Khair Al Shamaileh, Vijay Kumar Devabhaktuni, Naima Kaabouch
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Applied Sciences
Subjects:
unmanned aerial vehicle
GPS spoofing attacks
machine learning
dataset bias
hyperparameter tuning
dataset imbalance
Online Access:https://www.mdpi.com/2076-3417/13/1/383

Internet

https://www.mdpi.com/2076-3417/13/1/383

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