Towards Detection of Child Sexual Abuse Media: Categorization of the Associated Filenames

  • Alexander Panchenko
  • Richard Beaufort
  • Hubert Naets
  • Cédrick Fairon
Conference paper

DOI: 10.1007/978-3-642-36973-5_82

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7814)
Cite this paper as:
Panchenko A., Beaufort R., Naets H., Fairon C. (2013) Towards Detection of Child Sexual Abuse Media: Categorization of the Associated Filenames. In: Serdyukov P. et al. (eds) Advances in Information Retrieval. ECIR 2013. Lecture Notes in Computer Science, vol 7814. Springer, Berlin, Heidelberg

Abstract

This paper approaches the problem of automatic pedophile content identification. We present a system for filename categorization, which is trained to identify suspicious files on P2P networks. In our initial experiments, we used regular pornography data as a substitution of child pornography. Our system separates filenames of pornographic media from the others with an accuracy that reaches 91–97%.

Keywords

short text categorization P2P networks child pornography 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Alexander Panchenko
    • 1
  • Richard Beaufort
    • 1
  • Hubert Naets
    • 1
  • Cédrick Fairon
    • 1
  1. 1.Université catholique de LouvainLouvain-la-NeuveBelgium

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