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Filtering Email Addresses, Credit Card Numbers and Searching for Bitcoin Artifacts with the Autopsy Digital Forensics Software

2019-04-10Conference paper Open access
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datacite.subject.fosCiências Naturais::Ciências da Computação e da Informação
datacite.subject.fosEngenharia e Tecnologia::Outras Engenharias e Tecnologias
datacite.subject.sdg03:Saúde de Qualidade
datacite.subject.sdg08:Trabalho Digno e Crescimento Económico
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
datacite.subject.sdg10:Reduzir as Desigualdades
datacite.subject.sdg11:Cidades e Comunidades Sustentáveis
dc.contributor.authorDomingues, Patricio
dc.contributor.authorFrade, Miguel
dc.contributor.authorParreira, João Mota
dc.date.accessioned2025-10-22T11:05:46Z
dc.date.available2025-10-22T11:05:46Z
dc.date.issued2019-04-10
dc.descriptionEISBN - 9783030170653
dc.descriptionFonte: https://www.researchgate.net/publication/332330707_Filtering_Email_Addresses_Credit_Card_Numbers_and_Searching_for_Bitcoin_Artifacts_with_the_Autopsy_Digital_Forensics_Software
dc.descriptionConference name - 10th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2018; Conference date - 13 December 2018 - 15 December 2018; Conference code - 225239
dc.description.abstractEmail addresses and credit card numbers found on digital forensic images are frequently an important asset in a forensic casework. However, the automatic harvesting of these data often yields many false positives. This paper presents the Forensic Enhanced Analysis (FEA) module for the Autopsy digital forensic software. FEA aims to eliminate false positives of email addresses and credit card numbers harvested by Autopsy, thus reducing the workload of the forensic examiner. FEA also harvests potential Bitcoin public addresses and private keys and validates them by looking into Bitcoin’s blockchain for the transactions linked to public addresses. FEA explores the report functionality of Autopsy and allows exports in CSV, HTML and XLS formats. Experimental results over four digital forensic images show that FEA eliminates as many as of email addresses and of credit card numbers.eng
dc.description.sponsorshipThis work was partially supported by FCT, Instituto de Telecomunicações under project UID/EEA/50008/2013 and CIIC under project UID/CEC/04524/2016.
dc.identifier.citationDomingues, P., Frade, M., Parreira, J.M. (2020). Filtering Email Addresses, Credit Card Numbers and Searching for Bitcoin Artifacts with the Autopsy Digital Forensics Software. In: Madureira, A., Abraham, A., Gandhi, N., Silva, C., Antunes, M. (eds) Proceedings of the Tenth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2018). SoCPaR 2018. Advances in Intelligent Systems and Computing, vol 942. Springer, Cham. https://doi.org/10.1007/978-3-030-17065-3_32.
dc.identifier.doi10.1007/978-3-030-17065-3_32
dc.identifier.eissn2194-5365
dc.identifier.isbn9783030170646
dc.identifier.isbn9783030170653
dc.identifier.issn2194-5357
dc.identifier.urihttp://hdl.handle.net/10400.8/14353
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer Nature
dc.relationInstituto de Telecomunicações
dc.relation.hasversionhttps://link.springer.com/chapter/10.1007/978-3-030-17065-3_32
dc.relation.ispartofAdvances in Intelligent Systems and Computing
dc.relation.ispartofProceedings of the Tenth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2018)
dc.rights.uriN/A
dc.subjectdigital forensics
dc.subjectemail addresses
dc.subjectcredit card numbers
dc.subjectBitcoin
dc.titleFiltering Email Addresses, Credit Card Numbers and Searching for Bitcoin Artifacts with the Autopsy Digital Forensics Softwareeng
dc.typeconference paper
dspace.entity.typePublication
oaire.awardTitleInstituto de Telecomunicações
oaire.awardURIhttp://hdl.handle.net/10400.8/14168
oaire.citation.conferenceDate2018-12
oaire.citation.conferencePlacePorto, Portugal
oaire.citation.endPage10
oaire.citation.startPage1
oaire.citation.titleAdvances in Intelligent Systems and Computing
oaire.fundingStreamFinanciamento do Plano Estratégico de Unidades de I&D - 2013/2015 - OE
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aa
person.familyNameDomingues
person.familyNameFrade
person.givenNamePatrício
person.givenNameMiguel
person.identifier1234758
person.identifier.ciencia-idAA15-6185-C477
person.identifier.ciencia-idA512-9B28-1CEC
person.identifier.orcid0000-0002-6207-6292
person.identifier.orcid0000-0002-4405-7696
person.identifier.scopus-author-id13411315400
person.identifier.scopus-author-id24468034000
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Email addresses and credit card numbers found on digital forensic images are frequently an important asset in a forensic casework. However, the automatic harvesting of these data often yields many false positives. This paper presents the Forensic Enhanced Analysis (FEA) module for the Autopsy digital forensic software. FEA aims to eliminate false positives of email addresses and credit card numbers harvested by Autopsy, thus reducing the workload of the forensic examiner. FEA also harvests potential Bitcoin public addresses and private keys and validates them by looking into Bitcoin’s blockchain for the transactions linked to public addresses. FEA explores the report functionality of Autopsy and allows exports in CSV, HTML and XLS formats. Experimental results over four digital forensic images show that FEA eliminates as many as of email addresses and of credit card numbers.
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