Exploring Cellular Automata Learning: An Innovative Approach for Secure and Imperceptible Digital Image Watermarking

Bhat, IK; Qadir, F; Neshat, M; Gandomi, AH

Exploring Cellular Automata Learning: An Innovative Approach for Secure and Imperceptible Digital Image Watermarking

Bhat, IK Qadir, F Neshat, M

Gandomi, AH

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Publisher:: Institute of Electrical and Electronics Engineers (IEEE)
Publication Type:: Journal Article
Citation:: IEEE Access, 2024, PP, (99), pp. 1-1
Issue Date:: 2024-01-01

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Field	Value	Language
dc.contributor.author	Bhat, IK
dc.contributor.author	Qadir, F
dc.contributor.author	Neshat, M https://orcid.org/0000-0002-9537-9513
dc.contributor.author	Gandomi, AH
dc.date.accessioned	2024-10-09T03:35:10Z
dc.date.available	2024-10-09T03:35:10Z
dc.date.issued	2024-01-01
dc.identifier.citation	IEEE Access, 2024, PP, (99), pp. 1-1
dc.identifier.issn	2169-3536
dc.identifier.issn	2169-3536
dc.identifier.uri	http://hdl.handle.net/10453/181311
dc.description.abstract	As technology and multimedia production have advanced, there has been a significant rise in attacks on digital media, resulting in duplicated, fraudulent, and altered data as well as the infringement of copyright laws. This paper presents a robust and secure digital image watermarking technique that has been implemented in the spatial domain and exploits the erratic and chaotic behavior of the powerful elementary cellular automata Rule 30. This research is motivated by the potential to incorporate dynamic computational models into the field of image security. We aim to strike a balance between the crucial characteristics of the watermarking system, i.e., imperceptibility, capacity, and robustness, in the suggested blind watermarking technique. In this approach, prior to embedding, the grayscale watermark image is downsized to its two Most Significant Bits (MSBs). In the following, the 2-MSBs watermark is encrypted using an ECA Rule 30 to level up the system’s security attributes. Then, the host image is scrambled using ECA Rule 30 to distribute the watermark pixels throughout the host image and thus achieve the highest robustness against geometrical attacks. Finally, the encrypted watermark data is embedded into the scrambled host image using the ECA Rule 30-based embedding key. The proposed method performs better in terms of imperceptibility, capacity, and robustness when compared to several systems with similar competencies. The simulation’s findings demonstrate strong imperceptibility, as evaluated by the Peak Signal-to-Noise Ratio (PSNR), which has an average value of 58.3735 dB and a high payload. The experimental outcomes, observed across a diverse range of standardized attack scenarios, unequivocally establish the ascendancy of the proposed algorithm over competing methodologies in the realm of image watermarking.
dc.language	en
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartof	IEEE Access
dc.relation.isbasedon	10.1109/ACCESS.2024.3428362
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	08 Information and Computing Sciences, 09 Engineering, 10 Technology
dc.subject.classification	40 Engineering
dc.subject.classification	46 Information and computing sciences
dc.title	Exploring Cellular Automata Learning: An Innovative Approach for Secure and Imperceptible Digital Image Watermarking
dc.type	Journal Article
utslib.citation.volume	PP
utslib.for	08 Information and Computing Sciences
utslib.for	09 Engineering
utslib.for	10 Technology
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/UTS Groups
pubs.organisational-group	University of Technology Sydney/UTS Groups/Data Science Institute (DSI)
pubs.organisational-group	University of Technology Sydney/Strength - DSI - Data Science Institute
utslib.copyright.status	open_access	*
dc.rights.license	This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.license	This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.date.updated	2024-10-09T03:35:05Z
pubs.issue	99
pubs.publication-status	Published
pubs.volume	PP
utslib.citation.issue	99

Abstract:

As technology and multimedia production have advanced, there has been a significant rise in attacks on digital media, resulting in duplicated, fraudulent, and altered data as well as the infringement of copyright laws. This paper presents a robust and secure digital image watermarking technique that has been implemented in the spatial domain and exploits the erratic and chaotic behavior of the powerful elementary cellular automata Rule 30. This research is motivated by the potential to incorporate dynamic computational models into the field of image security. We aim to strike a balance between the crucial characteristics of the watermarking system, i.e., imperceptibility, capacity, and robustness, in the suggested blind watermarking technique. In this approach, prior to embedding, the grayscale watermark image is downsized to its two Most Significant Bits (MSBs). In the following, the 2-MSBs watermark is encrypted using an ECA Rule 30 to level up the system’s security attributes. Then, the host image is scrambled using ECA Rule 30 to distribute the watermark pixels throughout the host image and thus achieve the highest robustness against geometrical attacks. Finally, the encrypted watermark data is embedded into the scrambled host image using the ECA Rule 30-based embedding key. The proposed method performs better in terms of imperceptibility, capacity, and robustness when compared to several systems with similar competencies. The simulation’s findings demonstrate strong imperceptibility, as evaluated by the Peak Signal-to-Noise Ratio (PSNR), which has an average value of 58.3735 dB and a high payload. The experimental outcomes, observed across a diverse range of standardized attack scenarios, unequivocally establish the ascendancy of the proposed algorithm over competing methodologies in the realm of image watermarking.

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http://hdl.handle.net/10453/181311