Reconstructing Textual File Fragments Using Unsupervised Machine Learning Techniques

Reconstructing Textual File Fragments Using Unsupervised Machine Learning Techniques

This work is an investigation into reconstructing fragmented ASCII files based on content analysis motivated by a desire to demonstrate machine learning's applicability to Digital Forensics. Using a categorized corpus of Usenet, Bulletin Board Systems, and other assorted documents a series of e...

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Bibliographic Details
Main Author: Roux, Brian
Format: Others
Published: ScholarWorks@UNO 2008
Subjects:
Machine Learning
File Carving
Fragmented Files
Support Vector Machines
SVM
Digital Forensics
Information Retrieval
Online Access:http://scholarworks.uno.edu/td/881
http://scholarworks.uno.edu/cgi/viewcontent.cgi?article=1861&context=td

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http://scholarworks.uno.edu/td/881
http://scholarworks.uno.edu/cgi/viewcontent.cgi?article=1861&context=td

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