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Are You Really a Child?: A Machine Learning Approach To Protect Children from Online Grooming
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science. (Security)
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. (Security)
(Security)
2015 (English)In: Proc. National Symposium on Technology and Methodology for Security and Crisis Management: TAMSEC 2015, 2015Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

Online grooming and sexual abuse of children is a major threat towards the security of todays society where more and more time is spent online. To become friends and establish a relationship with their young victims in online communities, groomers often pretend to be children. In this work we describe an approach that can be used to detect if an adult is pretending to be a child in a chat room conversation. Our results show that even if it is hard to separate ordinary adults from children in chat logs it is possible to distinguish real children from adults pretending to be children with a high accuracy.

Place, publisher, year, edition, pages
2015.
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:uu:diva-272244OAI: oai:DiVA.org:uu-272244DiVA: diva2:893578
Conference
TAMSEC 2015, November 24–25, Kista, Sweden
Available from: 2016-01-12 Created: 2016-01-12 Last updated: 2016-07-29Bibliographically approved

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Ashcroft, MichaelKaati, Lisa

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