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Join security and block watermarking-based evolutionary algorithm and Racah moments for medical imaging

2024-10Journal article Restricted access
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dc.contributor.authorChekira, Chaimae
dc.contributor.authorMarzouq, Manal
dc.contributor.authorFadili, Hakim El
dc.contributor.authorLakhliai, Zakia
dc.contributor.authorRuano, Maria
dc.date.accessioned2025-01-08T11:00:16Z
dc.date.available2025-01-08T11:00:16Z
dc.date.issued2024-10
dc.description.abstractEnsuring the security of medical images containing confidential patient health information has become crucial. This paper presents a multipurpose medical image system based on a join of security and watermarking to achieve high data protection. We propose a block-splitting technique applied to large-scale cover medical images and hidden watermarks. In each subspace, we calculate Racah moments and apply a new evolutionary algorithm to automatically select the best positions for moments to be used for watermark hiding. This selection is based on a set of chromosomes with a specific coding strategy and evolutionary operators. The entire watermarked medical image is transmitted, and the extraction process is applied on the receiving side to recover the hidden watermark. Our method aims to achieve an optimal trade-off between watermarking requirements (imperceptibility and robustness) and enhance data protection by combining the proposed method with the three security services (confidentiality, integrity, and authentication). This hybrid combination uses high-performance encryption algorithms applied to the watermark components: the patient’s fingerprint, Electronic Record Patient, and doctor’s face. Watermarking performance and security services are evaluated using different medical datasets (DICOM, Figshare Brain Tumor, Covid-19, CXR, and MuRa images) in the absence of noise and against local or global noise. A comparative analysis with reliable and recent methods in medical image watermarking shows that our method achieves high performance: imperceptibility with a maximum PSNR of 46 dB, robustness with a maximum NC of 0.98, authentication with a maximum PSNR of 36.2 dB, and integrity with a maximum similarity of 0.97.eng
dc.identifier.doi10.1016/j.bspc.2024.106554
dc.identifier.issn1746-8094
dc.identifier.urihttp://hdl.handle.net/10400.1/26589
dc.language.isoeng
dc.peerreviewedyes
dc.publisherElsevier
dc.relationCENTRE FOR INFORMATICS AND SYSTEMS OF THE UNIVERSITY OF COIMBRA
dc.relationCENTRE FOR INFORMATICS AND SYSTEMS OF THE UNIVERSITY OF COIMBRA
dc.relation.ispartofBiomedical Signal Processing and Control
dc.rights.uriN/A
dc.subjectMedical imaging
dc.subjectBlind watermarking
dc.subjectRacah moments
dc.subjectEvolutionary algorithm
dc.subjectEncryption
dc.titleJoin security and block watermarking-based evolutionary algorithm and Racah moments for medical imagingeng
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleCENTRE FOR INFORMATICS AND SYSTEMS OF THE UNIVERSITY OF COIMBRA
oaire.awardTitleCENTRE FOR INFORMATICS AND SYSTEMS OF THE UNIVERSITY OF COIMBRA
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00326%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00326%2F2020/PT
oaire.citation.issueParte B
oaire.citation.startPage106554
oaire.citation.titleBiomedical Signal Processing and Control
oaire.citation.volume96
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameRuano
person.givenNameMaria
person.identifier.ciencia-id9811-A0DD-D5A5
person.identifier.orcid0000-0002-0014-9257
person.identifier.ridA-8321-2011
person.identifier.scopus-author-id7004483805
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
relation.isAuthorOfPublication61fc8492-d73f-46ca-a3a3-4cd762a784e6
relation.isAuthorOfPublication.latestForDiscovery61fc8492-d73f-46ca-a3a3-4cd762a784e6
relation.isProjectOfPublication83f2e15a-9149-4e1c-a58a-7dc58aba01eb
relation.isProjectOfPublicationa152be3d-c2bd-4132-ad1c-58b88dd373d7
relation.isProjectOfPublication.latestForDiscovery83f2e15a-9149-4e1c-a58a-7dc58aba01eb

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