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Automated Data Type Identification And Localization Using Statistical Analysis Data Identification

This research presents a new and unique technique called SÁDI, statistical analysis data identification, for identifying the type of data on a digital device and its storage format based on data type, specifically the values of the bytes representing the data being examined. This research incorporates the automation required for specialized data identification tools to be useful and applicable in real-world applications. The SÁDI technique utilizes the byte values of the data stored on a digital storage device in such a way that the accuracy of the technique does not rely solely on the potentially misleading metadata information but rather on the values of the data itself. SÁDI provides the capability to identify what digitally stored data actually represents. The identification of the relevancy of data is often dependent upon the identification of the type of data being examined. Typical file type identification is based upon file extensions or magic keys. These typical techniques fail in many typical forensic analysis scenarios, such as needing to deal with embedded data, as in the case of Microsoft Word files or file fragments. These typical techniques for file identification can also be easily circumvented, and individuals with nefarious purposes often do so.

Identiferoai:union.ndltd.org:UTAHS/oai:digitalcommons.usu.edu:etd-1009
Date01 December 2008
CreatorsMoody, Sarah Jean
PublisherDigitalCommons@USU
Source SetsUtah State University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceAll Graduate Theses and Dissertations
RightsCopyright for this work is held by the author. Transmission or reproduction of materials protected by copyright beyond that allowed by fair use requires the written permission of the copyright owners. Works not in the public domain cannot be commercially exploited without permission of the copyright owner. Responsibility for any use rests exclusively with the user. For more information contact Andrew Wesolek (andrew.wesolek@usu.edu).

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