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Comparing Pedophile Activity in Different P2P Systems

Bibliographic Data

ID5935429
AuthorsRaphaël Fournier (Université Sorbonne Paris Nord, corresponding author), Thibault Cholez (0000-0002-0435-3909, Centre Inria de l'Université de Lorraine), Matthieu Latapy (0000-0002-0975-6109, Centre National de la Recherche Scientifique), Isabelle Chrisment (Centre Inria de l'Université de Lorraine), Clémence Magnien (0000-0003-0320-4378, Centre National de la Recherche Scientifique), Olivier Festor (0000-0002-3181-7967, Centre Inria de l'Université de Lorraine), Ivan Daniloff (Centre National de la Recherche Scientifique)
Year2014
Volume3
Issue3
Pages314-325
Publication date2014-07-01
Open AccessYes
TypeARTICLE
VenueSocial Sciences (JOURNAL)
Journal identifiersISSN: 2076-0760 • E-ISSN: 2076-0760
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/socsci3030314
OpenAlexW2002339528
LanguageEN
Citations received1
References cited10

Peer-to-peer (P2P) systems are widely used to exchange content over the Internet. Knowledge of pedophile activity in such networks remains limited, despite having important social consequences. Moreover, though there are different P2P systems in use, previous academic works on this topic focused on one system at a time and their results are not directly comparable. We design a methodology for comparing KAD and eDonkey, two P2P systems among the most prominent ones and with different anonymity levels. We monitor two eDonkey servers and the KAD network during several days and record hundreds of thousands of keyword-based queries. We detect pedophile-related queries with a previously validated tool and we propose, for the first time, a large-scale comparison of pedophile activity in two different P2P systems. We conclude that there are significantly fewer pedophile queries in KAD than in eDonkey (approximately 0.09% vs. 0.25

Anonymity · Computer security · Scale (ratio · Server · The Internet · World Wide Web · Computer Science · Internet Traffic Analysis and Secure E-voting · Peer-to-Peer Network Technologies · Spam and Phishing Detection

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Citations per year0.11
Citation span2017 - 2017 (1)
Highly citedNo

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