METHOD AND DATA PROCESSING SYSTEM FOR MAKING MACHINE LEARNING MODEL MORE RESISTENT TO ADVERSARIAL EXAMPLES

METHOD AND DATA PROCESSING SYSTEM FOR MAKING MACHINE LEARNING MODEL MORE RESISTENT TO ADVERSARIAL EXAMPLES

A method and data processing system for making a machine learning model more resistant to adversarial examples are provided. In the method, an input for a machine learning model is provided. A randomly generated mask is added to the input to produce a modified input. The modified input is provided t...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Friedberger, Simon Johann, Van Vredendaal, Christine, Kuipers, Christiaan, Veshchikov, Nikita, Bos, Joppe Willem, Verneuil, Vincent, Ermans, Brian
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC COMMUNICATION TECHNIQUE
ELECTRICITY
PHYSICS
TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION
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Beschreibung
Zusammenfassung:A method and data processing system for making a machine learning model more resistant to adversarial examples are provided. In the method, an input for a machine learning model is provided. A randomly generated mask is added to the input to produce a modified input. The modified input is provided to the machine learning model. The randomly generated mask negates the effect of a perturbation added to the input for causing the input to be an adversarial example. The method may be implemented using the data processing system.