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IJMLC 2020 Vol.10(2): 277-282 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2020.10.2.932

Digital Watermarking Using Deep Neural Network

Farah Deeba, She Kun, Fayaz Ali Dharejo, Hameer Langah, and Hira Memon

Abstract—Recently in the vast advancement of Artificial Intelligence, Machine learning and Deep Neural Network (DNN) driven us to the robust applications. Such as Image processing, speech recognition, and natural language processing, DNN Algorithms has succeeded in many drawbacks; especially the trained DNN models have made easy to the researchers to produce state-of-art results. However, sharing these trained models are always a challenging task, i.e. security, and protection. We performed extensive experiments to present some analysis of watermark in DNN. We proposed a DNN model for Digital watermarking which investigate the intellectual property of Deep Neural Network, Embedding watermarks, and owner verification. This model can generate the watermarks to deal with possible attacks (fine-tuning and train to embed). This approach is tested on the standard dataset. Hence this model is robust to above counter-watermark attacks. Our model accurately and instantly verifies the ownership of all the remotely expanded deep learning models without affecting the model accuracy for standard information data.

Index Terms—Watermark, embedded, ownership verification, deep neural network.

Farah Deeba and She Kun are with the School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, China (e-mail: farahdeebauestc@hotmail.com, Kun@ uestc.edu.cn).
Fayaz Ali Dharejo is with the Computer Network Information Center, Chinese Academy of Sciences University of Chinese Academy of Sciences, Beijing, Haidian 100190, China (e-mail: fayazdharejo@cnic.cn).
Hmaeer Lnagah and Hira memon are with the Computer System Engineering, Quiad e Awam University of Engineering Science and Technology of Nawabshah, 67450, Pakistan (e-mail: hameer.langah@outlook.com, hiramemon09@gmail.com).


Cite: Farah Deeba, She Kun, Fayaz Ali Dharejo, Hameer Langah, and Hira Memon, "Digital Watermarking Using Deep Neural Network," International Journal of Machine Learning and Computing vol. 10, no. 2, pp. 277-282, 2020.

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • Frequency: Quaterly
  • DOI: 10.18178/IJML
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals LibraryCNKI.
  • E-mail: ijml@ejournal.net

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