ROSE: Extended Evaluation of RObust and SEcure Black-Box DNN Watermarking

ROSE is a black-box watermarking method (a technique to prove ownership of AI models by embedding hidden triggers that only the owner can activate) for protecting deep neural networks (DNNs, large AI models that learn patterns from data) in machine learning services. The method uses secret trigger-label pairs connected through a hash function to verify ownership while resisting attacks like fine-tuning, pruning, and other model modifications, while maintaining the model's performance on its original task.