An Improved Design Scheme for Perceptual Hashing Based on CNN for Digital Watermarking

Zhaoxiong Meng, Tetsuya Morizumi, Sumiko Miyata, Hirotsugu Kinoshita

研究成果: Conference contribution

抄録

Digital watermarking technology is used extensively in the field of digital rights management. However, there are a few problems when it comes to making effective use of digital watermarking. First, for conventional digital watermarking, a digital image is used only as a carrier for embedded watermarking information, and as this information may be diverted to other images, the watermark information needs to be generated based on the original image. Second, after the original image is modified/edited, the watermark information needs to prove that it is from the original image. Third, multiple digital watermarks need to be stored and managed without depending on trusted third parties. In an earlier work, we proposed a digital rights management system based on digital watermarking, blockchain, and perceptual hashing to resolve these issues. However, because we used conventional perceptual hashing, we could not draw sufficient conclusions about the first and second problems. In order to obtain a stable digest message of an image for digital watermarking, we here propose a new construction method for perceptual hashing using a convolutional neural network (CNN). In the proposed method, we first construct a machine-learned CNN for accepting an image that we want to take the perceptual hash value. The perceptual hash value is the cryptographic hash value of the weights that make up the CNN. We then verify that the reconstructed CNN can guarantee the hash value used when obtaining the hash value, and confirm that the image to be verified is accepted and is the perceptual hash value of this image.

本文言語English
ホスト出版物のタイトルProceedings - 2020 IEEE 44th Annual Computers, Software, and Applications Conference, COMPSAC 2020
編集者W. K. Chan, Bill Claycomb, Hiroki Takakura, Ji-Jiang Yang, Yuuichi Teranishi, Dave Towey, Sergio Segura, Hossain Shahriar, Sorel Reisman, Sheikh Iqbal Ahamed
出版社Institute of Electrical and Electronics Engineers Inc.
ページ1789-1794
ページ数6
ISBN(電子版)9781728173030
DOI
出版ステータスPublished - 2020 7
外部発表はい
イベント44th IEEE Annual Computers, Software, and Applications Conference, COMPSAC 2020 - Virtual, Madrid, Spain
継続期間: 2020 7 132020 7 17

出版物シリーズ

名前Proceedings - 2020 IEEE 44th Annual Computers, Software, and Applications Conference, COMPSAC 2020

Conference

Conference44th IEEE Annual Computers, Software, and Applications Conference, COMPSAC 2020
国/地域Spain
CityVirtual, Madrid
Period20/7/1320/7/17

ASJC Scopus subject areas

  • 人工知能
  • コンピュータ ネットワークおよび通信
  • コンピュータ サイエンスの応用
  • ハードウェアとアーキテクチャ
  • ソフトウェア
  • 教育

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