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Authentic Dialogue Generation to Improve Youth's Awareness of Cybergrooming for Online Safety
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  • Pei Wang ,
  • Zhen Guo ,
  • Lifu Huang ,
  • Jin-Hee Cho
Lifu Huang
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Jin-Hee Cho
Virginia Tech

Corresponding Author:[email protected]

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Abstract

This paper deals with a cybergrooming and sexual misconduct topic in artificial intelligence-based educational programs. Although cybergrooming has been recognized as a cybercrime, there is a lack of programs to protect youth from cybergrooming. We present a generative chatbot framework, SERI (Stop cybERgroomIng), that can generate fluent authentic conversations in the context of cybergrooming between a perpetrator chatbot and a potential victim chatbot. Furthermore, we propose deep-reinforcement-learning-based dialogue generation with a stage-related reward to lead the conversation to the expected stage. We also minimize potential ethical issues introduced by the perverted languages when deploying the chatbots for cybersecurity education programs. We evaluated the conversations of SERI with open-source referenced, unreferenced metrics and human evaluation. We developed SERI as a platform for deploying perpetrator chatbot to interact with youth users to observe their responses and collect reactions when they are asked for private or sensitive information by the perpetrator.