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Forensic Analysis of Tampered Digital Photos

2021Comunicação em conferência Acesso aberto
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datacite.subject.fosCiências Naturais::Matemáticas
datacite.subject.fosCiências Naturais::Ciências da Computação e da Informação
datacite.subject.sdg08:Trabalho Digno e Crescimento Económico
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
datacite.subject.sdg10:Reduzir as Desigualdades
dc.contributor.authorFerreira, Sara
dc.contributor.authorAntunes, Mário
dc.contributor.authorCorreia, Manuel E.
dc.date.accessioned2026-04-21T17:30:21Z
dc.date.available2026-04-21T17:30:21Z
dc.date.issued2021
dc.descriptionEISBN - 9783030934200
dc.description25th Iberoamerican Congress, CIARP 2021, May 10–13, 2021
dc.description.abstractDeepfake in multimedia content is being increasingly used in a plethora of cybercrimes, namely those related to digital kidnap, and ransomware. Criminal investigation has been challenged in detecting manipulated multimedia material, by applying machine learning techniques to distinguish between fake and genuine photos and videos. This paper aims to present a Support Vector Machines (SVM) based method to detect tampered photos. The method was implemented in Python and integrated as a new module in the widely used digital forensics application Autopsy. The method processes a set of features resulting from the application of a Discrete Fourier Transform (DFT) in each photo. The experiments were made in a new and large dataset of classified photos containing both legitimate and manipulated photos, and composed of objects and faces. The results obtained were promising and reveal the appropriateness of using this method embedded in Autopsy, to help in criminal investigation activities and digital forensics.eng
dc.identifier.citationFerreira, S., Antunes, M., Correia, M.E. (2021). Forensic Analysis of Tampered Digital Photos. In: Tavares, J.M.R.S., Papa, J.P., González Hidalgo, M. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2021. Lecture Notes in Computer Science(), vol 12702. Springer, Cham. https://doi.org/10.1007/978-3-030-93420-0_43.
dc.identifier.doi10.1007/978-3-030-93420-0_43
dc.identifier.eissn1611-3349
dc.identifier.isbn9783030934194
dc.identifier.isbn9783030934200
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/10400.8/16171
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer Nature
dc.relation.hasversionhttps://link.springer.com/chapter/10.1007/978-3-030-93420-0_43
dc.relation.ispartofLecture Notes in Computer Science
dc.relation.ispartofProgress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
dc.rights.uriN/A
dc.subjectDigital forensics
dc.subjectDeepfake
dc.subjectPhoto tampering
dc.subjectSupport Vector Machines
dc.subjectDiscrete Fourier Transform
dc.titleForensic Analysis of Tampered Digital Photoseng
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2021-05
oaire.citation.conferencePlacePorto, Portugal
oaire.citation.endPage470
oaire.citation.startPage461
oaire.citation.titleLecture Notes in Computer Science
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameAntunes
person.givenNameMário
person.identifierR-000-NX4
person.identifier.ciencia-idAF10-7EDD-5153
person.identifier.orcid0000-0003-3448-6726
person.identifier.scopus-author-id25930820200
relation.isAuthorOfPublicatione3e87fb0-d1d6-44c3-985d-920a5560f8c1
relation.isAuthorOfPublication.latestForDiscoverye3e87fb0-d1d6-44c3-985d-920a5560f8c1

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Deepfake in multimedia content is being increasingly used in a plethora of cybercrimes, namely those related to digital kidnap, and ransomware. Criminal investigation has been challenged in detecting manipulated multimedia material, by applying machine learning techniques to distinguish between fake and genuine photos and videos. This paper aims to present a Support Vector Machines (SVM) based method to detect tampered photos. The method was implemented in Python and integrated as a new module in the widely used digital forensics application Autopsy. The method processes a set of features resulting from the application of a Discrete Fourier Transform (DFT) in each photo. The experiments were made in a new and large dataset of classified photos containing both legitimate and manipulated photos, and composed of objects and faces. The results obtained were promising and reveal the appropriateness of using this method embedded in Autopsy, to help in criminal investigation activities and digital forensics.
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