Abstract: Embodiments of this specification provide methods and apparatuses for performing model ownership verification based on an exogenous feature. An implementation of the methods includes: selecting initial samples from an initial sample set to form a selected sample set, processing sample data of the initial samples to obtain transform samples that form a transform sample set, training a meta-classifier based on a target model, an auxiliary model, and the transform sample set, inputting data associated with a suspicious model into the meta-classifier, and determining, based on an output result of the meta-classifier, whether the suspicious model is stolen from a deployment model, wherein the deployment model has feature knowledge of the exogenous feature.

Abstract: Embodiments of the present specification provide a method, apparatus, and electronic device for preventing model theft during classification using a service classification model. The service classification model is a deep neural network for predicting a category of a service object, including an input layer, multiple intermediate layers, and an output layer that are sequentially stacked.

Abstract: Embodiments of the present specification provide a method, apparatus, and electronic device for preventing model theft during classification using a service classification model. The service classification model is a deep neural network for predicting a category of a service object, including an input layer, multiple intermediate layers, and an output layer that are sequentially stacked.