File Fragment Classification with Focus on OLE and OOXML classes (CROSBI ID 694542)
Prilog sa skupa u zborniku | ostalo | međunarodna recenzija
Podaci o odgovornosti
Skračić, Kristian ; Rukavina, Filip ; Miličić, Karlo ; Petrović, Juraj ; Pale, Predrag
engleski
File Fragment Classification with Focus on OLE and OOXML classes
Classification of file fragments is a crucial step in digital forensics and determining file types based on available data fragments. Currently explored file fragment classification methods other than forensic hand-examination rely on machine learning techniques. Those methods most commonly use features based on byte frequency distribution as inputs in artificial neural networks. In this paper, some new approaches to file fragment classification are explored. Older MS Office file format files (doc, ppt, and xls), and the new MS Office format (docx, pptx, and xlsx), which were previously shown to be difficult to differentiate between, were joined into two separate higher-level classes due to similarities in the included files’ structure. Different approaches to specifically differentiating between subtypes in each of those two higherlevel classes are further explored in the paper. The results suggest small increases in classification accuracy can be achieved using the proposed approach.
file fragment classification ; file type detection ; OLE ; OOXML ; artificial neural network ; feedforward neural network
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Podaci o prilogu
1507-1510.
2020.
objavljeno
10.23919/MIPRO48935.2020.9245428
Podaci o matičnoj publikaciji
Podaci o skupu
MIPRO 2020
predavanje
28.09.2020-02.10.2020
Opatija, Hrvatska