VMIFF - Visualization metrics for the identification of file fragments

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dc.contributor.advisor Yong Guan
dc.contributor.author Hartstack, Ellen
dc.contributor.department Electrical and Computer Engineering
dc.date 2018-07-21T03:56:56.000
dc.date.accessioned 2020-06-30T02:47:33Z
dc.date.available 2020-06-30T02:47:33Z
dc.date.copyright Tue Jan 01 00:00:00 UTC 2013
dc.date.embargo 2015-07-30
dc.date.issued 2013-01-01
dc.description.abstract <p>Visualization of complex data, such as a file system or file, allows a forensic analyst or reverse engineer to rapidly locate areas of interest amidst a large quantity of data. While visualization provides a promising form of analysis, is the subject of much skepticism, as human interaction is required in order for this method to be successful. As</p> <p>a result of this, visualization methods face two major obstacles: tediousness and time.</p> <p>As our contribution, we propose a unique method of graphing visual information into a measurable format suitable for use with machine learning algorithms. This method will still utilize the visual layout of the data but streamline this form into one that can be</p> <p>rapidly processed by a machine.</p> <p>In this work we examine existing methods of file fragment analysis, determine how to apply visualization to this analysis, and transform this visual data into a measurable format for machine leaning algorithms using our tool called VMIFF (Visualization Metrics for the Identification of File Fragments). In its breadth, this work aims to demonstrate that such transformations will still yield meaningful results.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/etd/13131/
dc.identifier.articleid 4138
dc.identifier.contextkey 4250778
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath etd/13131
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/27320
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/etd/13131/Hartstack_iastate_0097M_13456.pdf|||Fri Jan 14 19:45:20 UTC 2022
dc.subject.disciplines Computer Sciences
dc.subject.disciplines Databases and Information Systems
dc.subject.keywords File Fragments
dc.subject.keywords Forensics
dc.subject.keywords Identification
dc.subject.keywords Visualization
dc.title VMIFF - Visualization metrics for the identification of file fragments
dc.type article
dc.type.genre thesis
dspace.entity.type Publication
relation.isOrgUnitOfPublication a75a044c-d11e-44cd-af4f-dab1d83339ff
thesis.degree.level thesis
thesis.degree.name Master of Science
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