A Machine Learning Approach for Detecting Unauthorized Drone Operators

Abdulrahman Ahmad, Sultan Alameri, Youssef Ibrahim, Hasan Al Marzouqi

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    2 Scopus citations

    Abstract

    Governmental authorities worldwide have always been striving to impose further restrictions on the use of drones for safety reasons. On the other hand, hijackers always try to find a way to control the UAV to steal it, damage it or even assign tasks that are not meant to be operated. Classification of the UAV operators from the driving behavior is crucial to prevent malicious attacks and hijacking. This paper proposes a short-time prediction of unauthorized pilot behavior. A comprehensive analysis is conducted to find the optimal machine learning approach to classify the UAV operator in terms of accuracy, sensitivity, and prediction time. The utilized dataset consists of recorded flying sessions of 20 different pilots based on four features, thrust, yaw, pitch, and roll. To balance the dataset, the Synthetic Minority Over-sampling Technique (SMOTE) is utilized. A time-series forecasting approach is proposed to recognize repetitive patterns of pilot behavior over short time intervals. Finally, the proposed decision tree (DT) algorithm achieved the highest accuracy with 95% at a prediction time of 15 ms. The results outperformed state-of-the-art solutions for unauthorized pilot detection.

    Original languageBritish English
    Title of host publication2023 Advances in Science and Engineering Technology International Conferences, ASET 2023
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Electronic)9781665454742
    DOIs
    StatePublished - 2023
    Event2023 Advances in Science and Engineering Technology International Conferences, ASET 2023 - Dubai, United Arab Emirates
    Duration: 20 Feb 202323 Feb 2023

    Publication series

    Name2023 Advances in Science and Engineering Technology International Conferences, ASET 2023

    Conference

    Conference2023 Advances in Science and Engineering Technology International Conferences, ASET 2023
    Country/TerritoryUnited Arab Emirates
    CityDubai
    Period20/02/2323/02/23

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