Images are frequently met as evidence in Digital Forensics.  For example images are used in many legal cases concerning fraud, counterfeit, child pornography etc.

People who have reasons to hide potential evidence, often change extension and signature of an image in order to fool forensic software.

Identifying an altered image file, is therefore an interesting prospect as it would provide authorities and digital forensic examiners the enabling technology for the develpopment of a number of forensic applications.

The competition consists of two tasks:

  • File Type Identification and
  • Altered Image Identification.

We invite all researchers to register and participate in ICDAR 2017 Competition on File Type Identification. The second task is not obligatory, but we would be happy to see you participate to both tasks.  The description of the methods and the evaluation scores will be presented during a dedicated ICDAR 2017 contest session. A report on the competition will be published in the ICDAR 2017 conference proceedings.

Participants should find a detailed literature review in [1] regarding all recent trends in File Type Identification.  A recent work on file type detection can be found in [2]. A comparison of different classification algorithms concerning FTI methods, is available in [3].

[1]  K. Karampidis, G. Papadourakis and I. Deligiannis, “File Type Identification – A Literature Review,” in Proceedings of 9th International Conference on New Horizons in Industry, Business and Education, NHIBE 2015, Skiathos,Greece 2015​​
[2] Karampidis Konstantinos and Giorgios Papadourakis. “File Type Identification for Digital Forensics.” International Conference on Advanced Information Systems Engineering. Springer International Publishing, 2016.​
[3] Karampidis Konstantinos, Ergina Κavallieratou and Giorgos Papadourakis. “Comparison of Classification Algorithms for File Type Detection – A Digital Forensics Perspective” Accepted Paper, under publication in POLIBITS

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