Model Ownership Verification

Model ownership verification aims to protect the intellectual property of deep learning models by establishing irrefutable proof of ownership. Current research focuses on developing robust watermarking techniques, often embedding information within model explanations or using cryptographic signatures and zero-knowledge proofs to create verifiable ownership claims within federated learning settings. These methods strive to be both effective against model theft and harmless to the model's functionality, addressing concerns about false claims and ambiguity attacks. The development of secure and reliable ownership verification is crucial for incentivizing innovation and protecting the economic value of increasingly sophisticated AI models.