SSL-Auth: An Authentication Framework by Fragile Watermarking for Pre-trained Encoders in Self-supervised Learning. (arXiv:2308.04673v1 [cs.CR])

Self-supervised learning (SSL) which leverages unlabeled datasets for
pre-training powerful encoders has achieved significant success in recent
years. These encoders are commonly used as feature extractors for various
downstream tasks, requiring substantial data and computing resources for their
training process. With the deployment of pre-trained encoders in commercial
use, protecting the intellectual property of model owners and ensuring the
trustworthiness of the models becomes crucial. Recent research has shown that
encoders are threatened by backdoor attacks, adversarial attacks, etc.
Therefore, …

auth authentication computing data datasets deployment feature framework process resources ssl training watermarking