Using Approximate Matching to Reduce the Volume of Digital Data

Details

Serval ID
serval:BIB_5FB3F9090441
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Title
Using Approximate Matching to Reduce the Volume of Digital Data
Title of the conference
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Author(s)
Breitinger Frank, Winter Christian, Yannikos York, Fink Tobias, Seefried Michael
Publisher
Springer International Publishing
ISBN
9783319125671
9783319125688
ISSN
0302-9743
1611-3349
Publication state
Published
Issued date
2014
Editor
Peterson Gilbert, Shenoi Sujeet
Volume
433
Pages
149-163
Language
english
Abstract
Digital forensic investigators frequently have to search for relevant files in massive digital corpora – a task often compared to finding a needle in a haystack. To address this challenge, investigators typically apply cryptographic hash functions to identify known files. However, cryptographic hashing only allows the detection of files that exactly match the known file hash values or fingerprints. This paper demonstrates the benefits of using approximate matching to locate relevant files. The experiments described in this paper used three test images of Windows XP, Windows 7 and Ubuntu 12.04 systems to evaluate fingerprint-based comparisons. The results reveal that approximate matching can improve file identification – in one case, increasing the identification rate from 1.82% to 23.76%.
Keywords
File identification, approximate matching, ssdeep
Open Access
Yes
Create date
06/05/2021 12:01
Last modification date
06/05/2021 12:33
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