Titlebook: Digital Watermarking for Machine Learning Model; Techniques, Protocol Lixin Fan,Chee Seng Chan,Qiang Yang Book 2023 The Editor(s) (if appli

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Ownership Verification Protocols for Deep Neural Network Watermarkschemes, formulates several additional requirements regarding ownership proof under elementary protocols, and puts forward the necessity of analyzing and regulating the ownership verification procedure.

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拘留

Protecting Intellectual Property of Machine Learning Models via Fingerprinting the Classification Bo which are used to fingerprint the model. Another model is likely to be a pirated version of the owner’s model if they have the same predictions for most fingerprinting data points. The key difference between fingerprinting and watermarking is that fingerprinting . fingerprint that characterizes the

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Migratory

Protecting Recurrent Neural Network by Embedding Keyss to train RNN models in a specific way such that when an invalid or forged key is presented, the performance of the embedded RNN models will be .. Having said that, the key gate was inspired by the nature of RNN model, to govern the flow of hidden state and designed in such a way that no additional

Migratory

Model Auditing for Data Intellectual Propertyata owner cannot manage and thus cannot provide meaningful data ownership resolution. In this chapter, we rigorously present the model auditing problem for data ownership and open a new revenue in this area of research.

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1分開

https://doi.org/10.1057/9781137006509ermine whether a suspicious model is stolen from the victim, based on model gradients. The final ownership verification is judged by hypothesis test. Extensive experiments on CIFAR-10 and ImageNet datasets verify the effectiveness of our defense under both centralized training and federated learning

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