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Online Child Grooming Detection: Challenges and Future Directions
In the era of ever-growing online social networking communities, reports of online crimes of various forms and targeting are growing exponentially, highlighting the imperative need for the development and enforcement of solutions and measures aimed at early detection and prevention. Specifically, in today’s landscape, child sexual abuse (CSA) and especially online grooming activities are even more prominent given the more intense involvement of young people in these communities. Grooming detection techniques, designed using machine learning, have been at the forefront of prevention and protection of minors. However, current approaches face significant challenges that affect their efficacy and usability. In this chapter, we investigate the challenges faced towards creating effective grooming detection systems and propose future directions to be explored as part of CESAGRAM project’s response to child sexual abuse.
Online Child Grooming Detection: Challenges and Future Directions
In the era of ever-growing online social networking communities, reports of online crimes of various forms and targeting are growing exponentially, highlighting the imperative need for the development and enforcement of solutions and measures aimed at early detection and prevention. Specifically, in today’s landscape, child sexual abuse (CSA) and especially online grooming activities are even more prominent given the more intense involvement of young people in these communities. Grooming detection techniques, designed using machine learning, have been at the forefront of prevention and protection of minors. However, current approaches face significant challenges that affect their efficacy and usability. In this chapter, we investigate the challenges faced towards creating effective grooming detection systems and propose future directions to be explored as part of CESAGRAM project’s response to child sexual abuse.
Online Child Grooming Detection: Challenges and Future Directions
Security Informatics and Law Enforcement
Gkotsis, Ilias (Herausgeber:in) / Kavallieros, Dimitrios (Herausgeber:in) / Stoianov, Nikolai (Herausgeber:in) / Vrochidis, Stefanos (Herausgeber:in) / Diagourtas, Dimitrios (Herausgeber:in) / Akhgar, Babak (Herausgeber:in) / Mylonas, Nikolaos (Autor:in) / Stylianou, Nikolaos (Autor:in) / Chatzakou, Despoina (Autor:in) / Spathi, Theoni (Autor:in)
Paradigms on Technology Development for Security Practitioners ; Kapitel: 19 ; 237-247
30.09.2024
11 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Hosting service providers , Terrorist content online (TCO) , Hash sharing , NLP , Speech recognition , Classification , Computer vision , Explainable AI , Federated learning , TCO regulation , Removal order Physics , Security Science and Technology , Systems and Data Security , Computational Intelligence , Physics and Astronomy
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