Are You Really a Child?: A Machine Learning Approach To Protect Children from Online Grooming
2015 (English)In: Proc. National Symposium on Technology and Methodology for Security and Crisis Management: TAMSEC 2015, 2015Conference paper, Poster (Refereed)
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
Computer and Information Science
IdentifiersURN: urn:nbn:se:uu:diva-272244OAI: oai:DiVA.org:uu-272244DiVA: diva2:893578
TAMSEC 2015, November 24–25, Kista, Sweden