Steganalysis on Medical Images with Support Vector Machine

dc.authoridKarakis, Rukiye/0000-0002-1797-3461
dc.contributor.authorMaroof Ozcan, Fatmanur Betul
dc.contributor.authorKarakis, Rukiye
dc.contributor.authorGuler, Ivan
dc.date.accessioned2024-10-26T17:59:53Z
dc.date.available2024-10-26T17:59:53Z
dc.date.issued2020
dc.departmentSivas Cumhuriyet Üniversitesi
dc.description28th Signal Processing and Communications Applications Conference (SIU) -- OCT 05-07, 2020 -- ELECTR NETWORK
dc.description.abstractDICOM is a file format standard for medical images. DICOM file format includes a header with the patient's personal information as well as information related to the image. In steganography applications on medical data, patient's personal information, reports, and other data are hidden in the medical images. Steganalysis detects whether any secret data is hidden in a file or not. In this study, a steganalysis method is proposed to detect the presence of hidden data in a medical image. For this reason, the secret message that contains personal data extracted from the medical image header is embedded into the LSBs of the MR image pixels by using six different methods. The support vector machine (SVM) is used as a classifier for steganalysis between cover and stego images. As a result of the analysis, the presence of hidden data in medical images is found with 99.28% accuracy and 0.9856 correlation coefficient value.
dc.description.sponsorshipIstanbul Medipol Univ
dc.identifier.isbn978-1-7281-7206-4
dc.identifier.issn2165-0608
dc.identifier.urihttps://hdl.handle.net/20.500.12418/27404
dc.identifier.wosWOS:000653136100209
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.language.isotr
dc.publisherIEEE
dc.relation.ispartof2020 28th Signal Processing and Communications Applications Conference (Siu)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectmedical image steganography
dc.subjectDICOM
dc.subjectleast significant bit
dc.subjectsteganalysis
dc.subjectsupport vector machine
dc.titleSteganalysis on Medical Images with Support Vector Machine
dc.typeConference Object

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