Randomization Techniques to Mitigate the Risk of Copyright Infringement

In this work, we address the challenges in the Near Access Freeness (NAF) framework for copyright protection. We propose a Monte Carlo estimator to empirically measure the NAF bounds and conduct experiments to compare NAF-based solutions with differential privacy (DP)-based solutions, which impose stricter constraints. Finally, we introduce additional randomization techniques to enhance model ensemble methods, such as CP-(\Delta) and CP-(k).