DocumentCode
2510002
Title
File Fragment Classification-The Case for Specialized Approaches
Author
Roussev, Vassil ; Garfinkel, Simson L.
fYear
2009
fDate
21-21 May 2009
Firstpage
3
Lastpage
14
Abstract
Increasingly advances in file carving, memory analysis and network forensics requires the ability to identify the underlying type of a file given only a file fragment. Work to date on this problem has relied on identification of specific byte sequences in file headers and footers, and the use of statistical analysis and machine learning algorithms taken from the middle of the file. We argue that these approaches are fundamentally flawed because they fail to consider the inherent internal structure in widely used file types such as PDF, DOC, and ZIP. We support our argument with a bottom-up examination of some popular formats and an analysis of TK PDF files. Based on our analysis, we argue that specialized methods targeted to each specific file type will be necessary to make progress in this area.
Keywords
file organisation; TK PDF files; byte sequences; file carving; file footers; file fragment classification; file headers; machine learning algorithms; memory analysis; network forensics; statistical analysis; Clustering algorithms; Computer science; Conferences; Containers; Digital forensics; Frequency; Histograms; Machine learning algorithms; Statistical analysis; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Systematic Approaches to Digital Forensic Engineering, 2009. SADFE '09. Fourth International IEEE Workshop on
Conference_Location
Berkeley, CA
Print_ISBN
978-0-7695-3792-4
Type
conf
DOI
10.1109/SADFE.2009.21
Filename
5341545
Link To Document