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

FLASK

Protecting Intellectual Property of Machine Learning Models via Fingerprinting the Classification Bos such that it does not need to train its own model, which requires a large amount of resources. Therefore, it becomes an urgent problem how to distinguish such compromise of IP. Watermarking has been widely adopted as a solution in the literature. However, watermarking requires modification of the

消毒

水槽

Watermarks for Deep Reinforcement Learninging models, various watermarking approaches have been proposed. However, considering the complexity and stochasticity of reinforcement learning tasks, we cannot apply existing watermarking techniques for deep learning models to the deep reinforcement learning scenario directly. Existing watermarking

Mawkish

Ownership Protection for Image Captioning Modelster, we demonstrate that image captioning tasks cannot be adequately protected by the present digital watermarking architecture, which are generally considered as one of the most difficult AI challenges. To safeguard the image captioning model, we propose two distinct embedding strategies in the rec

remission

法律的瑕疵

FedIPR: Ownership Verification for Federated Deep Neural Network Modelsbution, and free-riding threat the collaboratively built models in federated learning. To address IP infringement issues, in this chapter, we introduce a novel deep neural network ownership verification framework for secure federated learning that allows each client to embed and extract private wate

幸福愉悦感

Model Auditing for Data Intellectual Propertye the model developer may illegally misuse or steal other party’s private data for training. To determine the data ownership from a trained deep neural network model, in this chapter, we propose a deep neural network auditing scheme that allows the auditor to trace illegal data usage from a trained

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Lixin Fan,Chee Seng Chan,Qiang YangThe first book to address the use of digital watermarking for verifying machine learning model ownerships.Presents essential protocols, methodologies and techniques for protecting machine learning mod

恶名声

Alcove

https://doi.org/10.1007/978-981-19-7554-7Machine learning model protection; deep learning model protection; model ownerhsip verification; model