MAP: MAsk-Pruning for Source-Free Model Intellectual Property Protection

arXiv:2403.04149v1 Announce Type: new
Abstract: Deep learning has achieved remarkable progress in various applications, heightening the importance of safeguarding the intellectual property (IP) of well-trained models. It entails not only authorizing usage but also ensuring the deployment of models in authorized data domains, i.e., making models exclusive to certain target domains. Previous methods necessitate concurrent access to source training data and target unauthorized data when performing IP protection, making them risky and inefficient for decentralized private data. In this paper, …

abstract applications arxiv cs.cv data deep learning deployment domains exclusive free importance intellectual property making map progress property protection pruning type usage