Exploring and validating data mining algorithms for use in data ascription
Huynh, Daniel P.
Garfinkel, Simson L.
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Digital forensics is a growing and important field of research for current intelligence, law enforcement, and military organizations today. As more information is stored in digital form, the need and ability to analyze and process this information for relevant evidence has grown in complexity. Today analysis is reliant upon trained experts. This, compounded with the sheer volume of evidence obtained from the field, means that analysis frequently takes too long. Current forensic tools focus on decoding and visualization and not data reduction or correlation. This thesis fills an important void. The first goal is to determine whether it is possible to use file metadata accurately to ascribe ownership of files based upon a hard drive with multiple users. The second is to explore and validate existing algorithms that may support and aid data ascription. The last goal of this work is to compare and measure the accuracy of these algorithms. This work facilitates further research into developing an automated analysis and reporting framework for media exploitation in computer forensics.