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dc.contributor.authorRowe, Neil C.
dc.dateJanuary 06, 2018
dc.date.accessioned2018-12-12T17:45:52Z
dc.date.available2018-12-12T17:45:52Z
dc.date.issued2018-01-06
dc.identifier.citationRowe, Neil C. "Finding and Rating Personal Names on Drives for Forensic Needs." International Conference on Digital Forensics and Cyber Crime. Springer, Cham, 2017.en_US
dc.identifier.urihttp://hdl.handle.net/10945/60805
dc.description.abstractPersonal names found on drives provide forensically valuable information about users of systems. This work reports on the design and engineering of tools to mine them from disk images, bootstrapping on output of the Bulk Extractor tool. However, most potential names found are either uninteresting sales and help contacts or are not being used as names, so we developed methods to rate name-candidate value by an analysis of the clues that they and their context provide. We used an empirically based approach with statistics from a large corpus from which we extracted 303 million email addresses and 74 million phone numbers, and then found 302 million personal names. We tested three machine-learning approaches and Naïve Bayes performed the best. Cross-modal clues from nearby email addresses improved performance still further. This approach eliminated from consideration 71.3% of the addresses found in our corpus with an estimated 67.4% F-score, a potential 3.5 times reduction in the name workload of most forensic investigations.en_US
dc.description.sponsorshipNaval Research Programen_US
dc.format.extent15 p.en_US
dc.publisherSpringerLinken_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleFinding and Rating Personal Names on Drives for Forensic Needsen_US
dc.typeArticleen_US
dc.contributor.corporateNaval Postgraduate School (U.S.)en_US
dc.contributor.departmentComputer Science (CS)
dc.subject.authorCross-modality
dc.subject.authorDigital forensicsen_US
dc.subject.authorPersonal namesen_US
dc.subject.authorExtractionen_US
dc.subject.authorEmail addresses Phone numbersen_US
dc.subject.authorRatingen_US
dc.subject.authorFilteringen_US
dc.subject.authorBulk Extractoren_US
dc.subject.authorNaïve Bayes Cross-modalityen_US


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