Towards detection of child sexual abuse media: categorization of the associated filenames

Authors:
Alexander Panchenko;Richard Beaufort;Hubert Naets;Cédrick Fairon
Affiliations:
Université catholique de Louvain, Louvain-la-Neuve, Belgium;Université catholique de Louvain, Louvain-la-Neuve, Belgium;Université catholique de Louvain, Louvain-la-Neuve, Belgium;Université catholique de Louvain, Louvain-la-Neuve, Belgium
Venue:
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Year:
2013

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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%.