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.
USING LSTM ENCODER-DECODER ALGORITHM FOR DETECTING ANOMALOUS ADS-B MESSAGES
2019-02-07
Patent
Electronic Resource
English
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 |
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