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

Zhaoxiong Meng, Tetsuya Morizumi, Sumiko Miyata, Hirotsugu Kinoshita

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE 44th Annual Computers, Software, and Applications Conference, COMPSAC 2020
EditorsW. K. Chan, Bill Claycomb, Hiroki Takakura, Ji-Jiang Yang, Yuuichi Teranishi, Dave Towey, Sergio Segura, Hossain Shahriar, Sorel Reisman, Sheikh Iqbal Ahamed
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1789-1794
Number of pages6
ISBN (Electronic)9781728173030
DOIs
Publication statusPublished - 2020 Jul
Event44th IEEE Annual Computers, Software, and Applications Conference, COMPSAC 2020 - Virtual, Madrid, Spain
Duration: 2020 Jul 132020 Jul 17

Publication series

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

Conference

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

Keywords

  • CNN
  • digital rights management
  • digital watermarking
  • perceptual hashing

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Software
  • Education

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