Research Output
Fingerprinting JPEGs With Optimised Huffman Tables
  A common task in digital forensics investigations is to identify known contraband images. This is typically achieved by calculating a cryptographic digest, using hashing algorithms such as SHA256, for each image on a given medium, and comparing individual digests with a database of known contraband. However, the large capacities of modern storage media and time pressures placed on forensics examiners necessitates the development of more efficient processing methods. This work describes a technique for fingerprinting JPEGs with optimised Huffman tables which requires only the image header to be present on the media. Such fingerprints are shown to be robust across large datasets, with demonstrably faster processing times.

  • Type:


  • Date:

    31 October 2018

  • Publication Status:


  • DOI:


  • ISSN:


  • Library of Congress:

    QA75 Electronic computers. Computer science

  • Dewey Decimal Classification:

    005.8 Data security

  • Funders:

    Edinburgh Napier Funded


McKeown, S., Russell, G., & Leimich, P. (2018). Fingerprinting JPEGs With Optimised Huffman Tables. Journal of Digital Forensics, Security and Law, 13(2),



digital forensics, image comparison, image processing, known file analysis, partial file analysis

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    Fingerprinting JPEGs with Optimised Huffman Tables


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