ChaSAM: An Architecture Based on Perceptual Hashing for Image Detection in Computer Forensics

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Autor(es): dc.contributorSão Paulo Scientific Police-
Autor(es): dc.contributorSão Paulo State Police-
Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.contributorEducation and Technology of São Paulo (IFSP)-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorBrock University-
Autor(es): dc.contributorState University of Southwest Bahia (UESB)-
Autor(es): dc.creatorSantos, Hericson Dos-
Autor(es): dc.creatorMartins, Tiago Dos Santos-
Autor(es): dc.creatorBarreto, Jorge Andre Domingues-
Autor(es): dc.creatorNakamura, Luis Hideo Vasconcelos-
Autor(es): dc.creatorRanieri, Caetano Mazzoni-
Autor(es): dc.creatorDe Grande, Robson E.-
Autor(es): dc.creatorFilho, Geraldo P. Rocha-
Autor(es): dc.creatorMeneguette, Rodolfo I.-
Data de aceite: dc.date.accessioned2025-08-21T19:26:42Z-
Data de disponibilização: dc.date.available2025-08-21T19:26:42Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2023-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/ACCESS.2024.3435027-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/303281-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/303281-
Descrição: dc.descriptionThe growing prevalence of digital crimes, especially those involving Child Sexual Abuse Material (CSAM) and revenge pornography, highlights the need for advanced forensic techniques to identify and analyze illicit content. While cryptographic hashing is commonly used in computer forensics, its effectiveness is often challenged because criminals can modify original information to create a new cryptographic hash. Perceptual hashes address this problem by focusing on the visual identity of the file rather than its bit-by-bit representation. This study introduces ChaSAM Forensics, a methodology that efficiently identifies illicit material using perceptual hashing techniques to track and identify illicit content, with a focus on child abuse material. Two new perceptual hashing algorithms, chHash and domiHash, were designed for integration into ChaSAM. The results showed that, under the tested conditions, the proposed chHash algorithm was more accurate than the established pHash algorithm when applied in a single iteration. Combinations of algorithms in two iterations were also assessed.-
Descrição: dc.descriptionSão Paulo Scientific Police-
Descrição: dc.descriptionSão Paulo State Police-
Descrição: dc.descriptionUniversity of São Paulo (USP) Institute of Mathematical and Computer Sciences-
Descrição: dc.descriptionFederal Institute of Science Education and Technology of São Paulo (IFSP)-
Descrição: dc.descriptionInstitute of Geosciences and Exact Sciences São Paulo State University (UNESP)-
Descrição: dc.descriptionBrock University Department of Computer Science-
Descrição: dc.descriptionState University of Southwest Bahia (UESB) Department of Exact and Technological Sciences-
Descrição: dc.descriptionInstitute of Geosciences and Exact Sciences São Paulo State University (UNESP)-
Formato: dc.format104611-104628-
Idioma: dc.languageen-
Relação: dc.relationIEEE Access-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectForensic computing-
Palavras-chave: dc.subjectimage detection-
Palavras-chave: dc.subjectperceptual hashing-
Palavras-chave: dc.subjectsimilarity-
Título: dc.titleChaSAM: An Architecture Based on Perceptual Hashing for Image Detection in Computer Forensics-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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