ADVERSARIAL SAMPLE PROTECTION FOR MACHINE LEARNING

Adversarial sample protection for machine learning is described. An example of a storage medium includes instructions for initiating processing of examples for training of an inference engine in a system; dynamically selecting a subset of defensive preprocessing methods from a repository of defensiv...

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Bibliographic Details
Main Authors KELLERMANN, Raizy, NAYSHTUT, Alex, LEVY, Dor, BEN-SHALOM, Omer
Format Patent
LanguageEnglish
French
German
Published 28.06.2023
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Summary:Adversarial sample protection for machine learning is described. An example of a storage medium includes instructions for initiating processing of examples for training of an inference engine in a system; dynamically selecting a subset of defensive preprocessing methods from a repository of defensive preprocessing methods for a current iteration of processing, wherein a subset of defensive preprocessing methods is selected for each iteration of processing; performing training of the inference engine with a plurality of examples, wherein the training of the inference engine include operation of the selected subset of defensive preprocessing methods; and performing an inference operation with the inference engine, including utilizing the selected subset of preprocessing defenses for the current iteration of processing.
Bibliography:Application Number: EP20220201179