From Attack to Protection: Leveraging Watermarking Attack Network for Advanced Add-on Watermarking

Fuente: arXiv
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Hauptverfasser: Nam, Seung-Hun, Kang, Jihyeon, Kim, Daesik, Ahn, Namhyuk, Ahn, Wonhyuk
Format: Preprint
Veröffentlicht: 2020
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author Nam, Seung-Hun
Kang, Jihyeon
Kim, Daesik
Ahn, Namhyuk
Ahn, Wonhyuk
author_facet Nam, Seung-Hun
Kang, Jihyeon
Kim, Daesik
Ahn, Namhyuk
Ahn, Wonhyuk
contents Multi-bit watermarking (MW) has been designed to enhance resistance against watermarking attacks, such as signal processing operations and geometric distortions. Various benchmark tools exist to assess this robustness through simulated attacks on watermarked images. However, these tools often fail to capitalize on the unique attributes of the targeted MW and typically neglect the aspect of visual quality, a critical factor in practical applications. To overcome these shortcomings, we introduce a watermarking attack network (WAN), a fully trainable watermarking benchmark tool designed to exploit vulnerabilities within MW systems and induce watermark bit inversions, significantly diminishing watermark extractability. The proposed WAN employs an architecture based on residual dense blocks, which is adept at both local and global feature learning, thereby maintaining high visual quality while obstructing the extraction of embedded information. Our empirical results demonstrate that the WAN effectively undermines various block-based MW systems while minimizing visual degradation caused by attacks. This is facilitated by our novel watermarking attack loss, which is specifically crafted to compromise these systems. The WAN functions not only as a benchmarking tool but also as an add-on watermarking (AoW) mechanism, augmenting established universal watermarking schemes by enhancing robustness or imperceptibility without requiring detailed method context and adapting to dynamic watermarking requirements. Extensive experimental results show that AoW complements the performance of the targeted MW system by independently enhancing both imperceptibility and robustness.
format Preprint
id arxiv_https___arxiv_org_abs_2008_06255
institution arXiv
publishDate 2020
record_format arxiv
spellingShingle From Attack to Protection: Leveraging Watermarking Attack Network for Advanced Add-on Watermarking
Nam, Seung-Hun
Kang, Jihyeon
Kim, Daesik
Ahn, Namhyuk
Ahn, Wonhyuk
Multimedia
Cryptography and Security
Computer Vision and Pattern Recognition
Multi-bit watermarking (MW) has been designed to enhance resistance against watermarking attacks, such as signal processing operations and geometric distortions. Various benchmark tools exist to assess this robustness through simulated attacks on watermarked images. However, these tools often fail to capitalize on the unique attributes of the targeted MW and typically neglect the aspect of visual quality, a critical factor in practical applications. To overcome these shortcomings, we introduce a watermarking attack network (WAN), a fully trainable watermarking benchmark tool designed to exploit vulnerabilities within MW systems and induce watermark bit inversions, significantly diminishing watermark extractability. The proposed WAN employs an architecture based on residual dense blocks, which is adept at both local and global feature learning, thereby maintaining high visual quality while obstructing the extraction of embedded information. Our empirical results demonstrate that the WAN effectively undermines various block-based MW systems while minimizing visual degradation caused by attacks. This is facilitated by our novel watermarking attack loss, which is specifically crafted to compromise these systems. The WAN functions not only as a benchmarking tool but also as an add-on watermarking (AoW) mechanism, augmenting established universal watermarking schemes by enhancing robustness or imperceptibility without requiring detailed method context and adapting to dynamic watermarking requirements. Extensive experimental results show that AoW complements the performance of the targeted MW system by independently enhancing both imperceptibility and robustness.
title From Attack to Protection: Leveraging Watermarking Attack Network for Advanced Add-on Watermarking
topic Multimedia
Cryptography and Security
Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2008.06255