A method for detecting anomalous ADS-B messages in airplanes and air-traffic control system, comprising: extracting features from application level data, which is information broadcasted in said ADS-B messages, contextual data and flight plans; analyzing said extracted features and computing relative measures of a flight based on said extracted features; training a machine learning model to represent a benign ADS-B messages; applying said machine learning model on said extracted features thereby deriving a reputation score for said ADS-B message; issuing a decision based on said score, thereby recognizing an attack and issuing an alarm regarded said recognized attack.


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    Title :

    Using LSTM encoder-decoder algorithm for detecting anomalous ADS-B messages


    Contributors:
    SHABTAI ASAF (author) / HABLER IDAN (author)

    Publication date :

    2021-07-20


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS



    USING LSTM ENCODER-DECODER ALGORITHM FOR DETECTING ANOMALOUS ADS-B MESSAGES

    SHABTAI ASAF / HABLER IDAN | European Patent Office | 2019

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