ASPG Menu
search

American Scientific Publishing Group

verified Journal

Journal of Artificial Intelligence and Metaheuristics

ISSN
Online: 2833-5597
Frequency

Continuous publication

Publication Model

Open access journal. All articles are freely available online with no APC.

Journal of Artificial Intelligence and Metaheuristics
Full Length Article

Volume 1Issue 2PP: 24-30 • 2022

Watermarking Models and Artificial Intelligence

B. M. El-den 1* ,
Marwa M. Eid 2
1Department of Electronics and Communication Engineering, Faculty of Engineering, Delta University for Science& Technology, International Coastal Road, Gamasah City, Mansoura, Dakhliya, Egypt,
2Faculty of Artifcial Intelligence, Delta University for Science and Technology, Mansoura, Egypt
* Corresponding Author.
Received: February 27, 2022 Accepted: July 02, 2022

Abstract

Machine learning and deep learning are good bets for solving various intelligence-related problems. While it has practical applications in watermarking, it performs less well on more standard tasks like prediction, classification, and regression. This article offers the results of a thorough investigation into watermarking using modern tools like AI, ML, and DL. Watermarking's origins, some historical context, and the most fascinating and practical applications are also covered briefly.

Keywords

Steganography digital watermarking data hiding applications fingerprint Deep Neural Networks

References

[1] W. Bender, D. Gruhl, N. Morimoto, A. Lu Techniques for data hiding IBM Syst. J., 35 (1996), pp. 313-336

CrossRefView Record in Scopus Google Scholar

[2] Cox, I.; Miller, M.; Jeffrey, A.; Fridrich, J.; Kalker, T. Digital Watermarking and Steganography, 2nd ed.;

Morgan Kaufmann: Burlington, MA, USA, 2008. [CrossRef]

[3] Megías, D. Data hiding: New opportunities for security and privacy? In Proceedings of the European

Interdisciplinary Cybersecurity Conference (EICC 2020), Rennes, France, 18 November 2020; Article No.: 15.

pp. 1–6. [CrossRef].

[4] Cox, I.; Miller, M.; Bloom, J.; Fridrich, J.; Kalker, T. Digital Watermarking and Steganography, 2nd ed.;

Morgan Kaufmann Publishers Inc.: San Francisco, CA, USA, 2007.

[5] Katzenbeisser, S.; Petitcolas, F.A. Information Hiding Techniques for Steganography and Digital Watermarking,

1st ed.; Artech House, Inc.: Norwood, MA, USA, 2000.

[6] Ibrahim, Abdelhameed, and El-Sayed M. El-kenawy. "Applications and datasets for superpixel techniques: A

survey." Journal of Computer Science and Information Systems 15, no. 3 (2020): 1-6.

[7] Eid, Marwa M., El-Sayed M. El-kenawy, and Abdelhameed Ibrahim. "A binary sine cosine-modified whale

optimization algorithm for feature selection." In 2021 National Computing Colleges Conference (NCCC), pp. 1-

6. IEEE, 2021.

[8] Qureshi, A.; Megías, D.; Rifà-Pous, H. Framework for Preserving Security and Privacy in Peer-to-Peer Content

Distribution Systems. Expert Syst. Appl. 2015, 42, 1391–1408. [CrossRef]

[9] Mehdi Hussain, Ainuddin Wahid Abdul Wahab, Yamani Idna Bin Idris, Anthony T.S. Ho, and Ki-Hyun Jung.

2018. Image steganography in spatial domain: A survey. Signal Processing: Image Communication 65 (2018),

46–66. https://doi.org/10.1016/j.image.2018.03.012

[10] Inas Jawad Kadhim, Prashan Premaratne, Peter James Vial, and Brendan Halloran. 2019. Comprehensive survey

of image steganography: Techniques, Evaluations, and trends in future research. Neurocomputing 335 (2019),

299–326.

[11] El-Sayed Towfek, M., and M. Saber El-kenawy. "Reham Arnous. An Integrated Framework to Ensure

Information Security Over the Internet." International Journal of Computer Applications 178, no. 29 (2019): 13-

15.

[12] Haribabu Kandi, Deepak Mishra, and Subrahmanyam R.K. Sai Gorthi. 2017. Exploring the learning capabilities

of convolutional neural networks for robust image watermarking. Computers & Security 65 (2017), 247–268.

HTTPS: //doi.org/10.1016/j.cose.2016.11.016

[13] Xiyang Luo, Yinxiao Li, Huiwen Chang, Ce Liu, Peyman Milanfar, and Feng Yang. 2021. DVMark: A Deep

Multiscale Framework for Video Watermarking. (04 2021).

[14] Innfarn Yoo, Huiwen Chang, Xiyang Luo, O. Stava, Ce Liu, P. Milanfar, and Feng Yang. 2021. Deep 3D-to-2D

Watermarking: Embedding Messages in 3D Meshes and Extracting Them from 2D Renderings. ArXiv

abs/2104.13450 (2021).

[15] Jiren Zhu, Russell Kaplan, Justin Johnson, and Li Fei-Fei. 2018. Hidden: Hiding Data with Deep Networks. In

Proceedings of the European Conference on Computer vision (ECCV 2018). 657–672.

[16] El-Kenawy, El-Sayed M., Marwa Eid, and Alshimaa H. Ismail. "A New Model for Measuring Customer Utility

Trust in Online Auctions." International Journal of Computer Applications 975: 8887.

[17] Xiyang Luo, Ruohan Zhan, Huiwen Chang, Feng Yang, and Peyman Milanfar. 2020. Distortion Agnostic Deep

Watermarking. Computer Vision Foundation (2020). arXiv:2001.04580 [cs.MM].

[18] Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron

Courville, and Yoshua Bengio. 2014. Generative Adversarial Networks. Advances in Neural Information

Processing Systems 3, 11 (2014). arXiv:1406.2661 [stat.ML]

[19] Das, Kajaree, and Rabi Narayan Behera. "A survey on machine learning: concept, algorithms and applications."

International Journal of Innovative Research in Computer and Communication Engineering 5, no. 2 (2017):

1301-1309.

[20] El-kenawy, El-Sayed M., Marwa M. Eid, and Abdelhameed Ibrahim. "Anemia estimation for covid-19 patients

using a machine learning model." Journal of Computer Science and Information Systems 17, no. 11 (2021):

2535-1451.

[21] Kavitha, R.S.; Eranna, U.; Giriprasad, M.N. DCT-DWT Based DigitalWatermarking and Extraction using Neural

Networks. In 556Proceedings of the 2020 International Conference on Artificial Intelligence and Signal

Processing (AISP); IEEE: Amaravati, India, 5572020; pp. 1–5.

[22] Ibrahim, Abdelhameed, Seyedali Mirjalili, Mohammed El-Said, Sherif SM Ghoneim, Mosleh M. Al-Harthi,

Tarek F. Ibrahim, and El-Sayed M. El-Kenawy. "Wind speed ensemble forecasting based on deep learning using

adaptive dynamic optimization algorithm." IEEE Access 9 (2021): 125787-125804.

[23] D. Sukheja, J. A. Shah, G. Madhu, K. Sandeep Kautish, F. A. Alghamdi et al., "New decision-making technique

based on hurwicz criteria for fuzzy ranking," Computers, Materials & Continua, vol. 73, no.3, pp. 4595–4609,

2022.

[24] Frattolillo, F. A Watermarking Protocol Based on Blockchain. Applied Sciences 2020, 10, 7746.

Cite This Article

Choose your preferred format

format_quote
El-den, B. M., Eid, Marwa M.. "Watermarking Models and Artificial Intelligence." Journal of Artificial Intelligence and Metaheuristics, vol. Volume 1, no. Issue 2, 2022, pp. 24-30. DOI: https://doi.org/10.54216/JAIM.010203
El-den, B., Eid, M. (2022). Watermarking Models and Artificial Intelligence. Journal of Artificial Intelligence and Metaheuristics, Volume 1(Issue 2), 24-30. DOI: https://doi.org/10.54216/JAIM.010203
El-den, B. M., Eid, Marwa M.. "Watermarking Models and Artificial Intelligence." Journal of Artificial Intelligence and Metaheuristics Volume 1, no. Issue 2 (2022): 24-30. DOI: https://doi.org/10.54216/JAIM.010203
El-den, B., Eid, M. (2022) 'Watermarking Models and Artificial Intelligence', Journal of Artificial Intelligence and Metaheuristics, Volume 1(Issue 2), pp. 24-30. DOI: https://doi.org/10.54216/JAIM.010203
El-den B, Eid M. Watermarking Models and Artificial Intelligence. Journal of Artificial Intelligence and Metaheuristics. 2022;Volume 1(Issue 2):24-30. DOI: https://doi.org/10.54216/JAIM.010203
B. El-den, M. Eid, "Watermarking Models and Artificial Intelligence," Journal of Artificial Intelligence and Metaheuristics, vol. Volume 1, no. Issue 2, pp. 24-30, 2022. DOI: https://doi.org/10.54216/JAIM.010203
Digital Archive Ready