Collusion Attack Resilient 3D Mesh Watermarking Based on Anti-Collusion Fingerprint Code

Abstract

Collusion attack is one of the techniques used for unauthorized removal of embedded marks. However, there are no algorithms that utilize the averaging-resilient fingerprint code into 3D mesh watermarking. In this paper, we propose a collusion resilient 3D mesh watermark based on mesh spectral analysis and the anti-collusion fingerprint code. We present two fingerprint schemes by exploiting the theoretically proven anti-collusion codes: the group-divisible partially balanced incomplete block design, and Tardos's fingerprint code. The proposed extraction scheme not only met the requirement for an anti-collusion code but also provided sufficient length of the payload for the fingerprint code. To minimize the detection error, we also modeled the response of the detector and herein present optimized thresholds for our method. Based on the experiments with public benchmarks, the proposed method outperformed conventional robust mesh watermarking against collusion attack, and provided robustness to the combination of a small amount of added noise and collusion attack.