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Conference Paper Personalized Response System for Different Voice Phishing Types: Utilizing a Retrieval-Augmented Generation Model
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Authors
Jeong-Min Lee, Yujin Baek, Myung-Sun Baek, Hyunho Park, Sungwon Byon, Eui-Suk Jung
Issue Date
2024-10
Citation
International Conference on Information and Communication Technology Convergence (ICTC) 2024, pp.699-702
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTC62082.2024.10827466
Abstract
This study presents the development of a comprehensive system designed to effectively classify voice phishing types and provide personalized response manuals tailored to specific scenarios. By integrating a binary classification model with a Retrieval-Augmented Generation (RAG) model, our system offers a dynamic solution to combat the evolving threats of voice phishing. The system’s ability to generate situation-specific response manuals demonstrates a significant advancement in preventive security measures. Upon receiving voice phishing conversation data, the system classifies the type of phishing attempt and provides tailored response instructions based on the classified scenario. This approach highlights the system’s potential as a practical tool for both enhancing security measures and providing educational resources.
KSP Keywords
Binary Classification, Classification models, Comprehensive system, Dynamic solution, Generation model, educational resources, response system, security measures