T2S: A Rehearsal-Based Approach for Extraction-Resistant Model Watermarking
Researchers propose T2S, a rehearsal-based watermarking framework that protects AI models against extraction attacks by simulating the theft process during training. The method embeds watermarks that remain detectable even when adversaries steal and replicate models, addressing a critical vulnerability in AI intellectual property protection.