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A New Approach to Compressed File Fragment Identification

  • Khoa NguyenEmail author
  • Dat Tran
  • Wanli Ma
  • Dharmendra Sharma
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 369)

Abstract

Identifying the underlying type of a file given only a file fragment is a big challenge in digital forensics. Many methods have been applied to file type identification; however the identification accuracies of most of file types are still very low, especially for files having complex structures because their contents are compound data built from different data types. In this paper, we propose a new approach based on the deflate-encoded data detection, entropy-based clustering, and the use of machine learning techniques to identify deflate-encoded file fragments. Experiments on the popular compound file type showed high identification accuracy for the proposed method.

Keywords

File fragment classification Compressed file fragment classification SVM Shannon entropy 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Khoa Nguyen
    • 1
    Email author
  • Dat Tran
    • 1
  • Wanli Ma
    • 1
  • Dharmendra Sharma
    • 1
  1. 1.Faculty of Education Science Technology and MathematicsUniversity of CanberraCanberraAustralia

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