An Intelligent Online Grooming Detection System Using AI Technologies

Philip Anderson, Zheming Zuo, Longzhi Yang, Yanpeng Qu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)
44 Downloads (Pure)

Abstract

The rapid expansion of the Internet has experienced a significant increase in cases of child abuse, as more and more young children have greater access to the Internet. In particular, adults and minors are able to exchange sexually explicit messages and media via a variety of online platforms that are widely available, which leads to an increasing concern of child grooming. Traditionally, the identification of child grooming relies on the analysis and localisation of conversation texts, but this is usually time-consuming and associated with other implications such as psychological pressure on the investigators. Therefore, automatic methods to detect grooming conversations have attracted the attention of many researchers. This paper proposes such a system to identify child grooming in online chat conversations, where the training data of the system were harvested from publicly available information. The data processing is based on a group of AI technologies, including fuzzy-rough feature selection and fuzzy twin support vector machine. Evaluation shows the promise of the proposed approach in identifying online grooming conversations to be implemented in the future after further development to support real-world cases.
Original languageEnglish
Title of host publication2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Place of PublicationPiscataway, NJ
PublisherIEEE
Number of pages6
ISBN (Electronic)9781538617281
ISBN (Print)9781538617298
DOIs
Publication statusPublished - 23 Jun 2019
Event2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) - JW Marriot New Orleans, New Orleans, United States
Duration: 23 Jun 201926 Jun 2019

Conference

Conference2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Abbreviated titleFUZZ-IEEE 2019
CountryUnited States
CityNew Orleans
Period23/06/1926/06/19

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