Note

IWDW 2020 participants have been granted a four-week free online access starting July 1st to the proceedings, which are available at https://link.springer.com/book/10.1007/978-3-030-69449-4.

Introduction

The 19th International Workshop on Digital-forensics and Watermarking (IWDW 2020) is a premier forum for researchers and practitioners working on novel researches, developments and applications of digital watermarking and forensics techniques for multimedia security. IWDW 2020 is organized by the Digital Research & Innovation Capability Platform at Swinburne University of Technology, Australia and the State Key Laboratory of Information Security at Institute of Information Engineering, Chinese Academy of Sciences.

We invite submissions of high-quality original research papers. Each submitted paper will be reviewed by at least 2 reviewers. Two prizes are to be awarded to the best paper and the best student paper, respectively. The proceedings of IWDW 2020 will be published on the Lecture Notes in Computer Science (LNCS) by Springer.

Important Notification: Due to the persistent Covid-19 epidemic situation, IWDW 2020 will be held as an online virtual conference. At least one of the authors of an accepted paper should register the workshop as an Author and deliver an online report on the paper. Other people, either co-authors or anyone else, can register and then attend the workshop freely as a Non-Author. The detailed information on the program will be posted on this website soon.

Click here for a PDF version of the Call for Papers.

For authors having an accepted paper, click here for the Springer copyright form.

Important Dates

Paper Submissions: 20 July 2020  10 August 2020   28 August 2020

Notification of Paper Acceptance: 1 September 2020  10 September 2020   28 September 2020

Camera-Ready Paper Due:  10 October 2020   28 October 2020

Topics of Interest

The topics of interest include, but are not limited to

  • Authentication, Copyright protection, DRM, and forensic watermarking
  • Channel coding techniques for watermarking
  • Convolutional neural networks (CNN) and deep learning for multimedia security
  • Combination of data hiding and cryptography
  • Fake multimedia forensics and anti-forensics
  • AI generated multimedia and detection of them
  • Information theoretic, stochastic and capacity aspects of data hiding
  • Large-scale experimental tests and benchmarking
  • Deepfake videos and detection of them
  • Statistical and perceptual models of multimedia content for multimedia security
  • Reversible data hiding
  • Robust perceptual hashing
  • Security issues in multimedia protection, including attacks and counter-attacks
  • Steganography and steganalysis
  • Source identification
  • Visual cryptography and secret image sharing

Contacts

Email address:

Paper submission: Dr. Hong Zhang, zhanghong@iie.ac.cn

Local Arrangement: Prof. Yang Xiang, yxiang@swin.edu.au

Website:

www.iwdw.site