NDLI: File Block Classification by Support Vector Machine

Content Provider	IEEE Xplore Digital Library
Author	Sportiello, L. Zanero, S.
Copyright Year	2011
Abstract	Retrieval of files without the support of file system structures is arguably essential for digital forensics. Files are typically stored as sequences of data blocks, which have to be reconstructed in the retrieval process. This is commonly performed, among other approaches, through file carving, in general detecting the original block sequences by means of signatures of known headers and footers of files. Of course, this creates challenges with fragmented files, where blocks belonging to different files may be interleaved. Ways to classify file blocks into file types relying on their content may provide a support to achieve a successful reconstruction. We propose to classify file blocks using Support Vector Machines (SVMs), and we do so by studying in-depth the impact of an appropriate selection of the features used in the classification process. We analyze several potential features and test their performance over a large and representative collection of file blocks and file types. We find out that SVM classifiers can achieve a good accuracy and that a specific type of features (based on byte frequency distribution) performs well across almost all of the examined file types.
Starting Page	307
Ending Page	312
File Size	193345
Page Count	6
File Format	PDF
ISBN	9781457709791
DOI	10.1109/ARES.2011.52
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-22
Publisher Place	Austria
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Training Computational modeling File Block Classification Feature extraction Entropy File Carving Complexity theory Mathematical model Machine Learning Forensic Analysis
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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