Emoti-Shing: Detecting Vishing Attacks by Learning Emotion Dynamics through Hidden Markov Models

作     者：Virgile Simé Nyassi Franklin Tchakounté Blaise Omer Yenké Duplex Elvis Houpa Danga Magnuss Dufe Ngoran Jean Louis Kedieng Ebongue Fendji Virgile Simé Nyassi;Franklin Tchakounté;Blaise Omer Yenké;Duplex Elvis Houpa Danga;Magnuss Dufe Ngoran;Jean Louis Kedieng Ebongue Fendji

作者机构：Department of Mathematics and Computer Science Faculty of Science University of Ngaoundr Ngaoundr Cameroon Department of Computer Engineering University Institute of Technology University of Ngaoundr Ngaoundr Cameroon 

出 版 物：《Journal of Intelligent Learning Systems and Applications》 (智能学习系统与应用（英文）)

年 卷 期：2024年第16卷第3期

页      面：274-315页

学科分类：0502[文学-外国语言文学] 050201[文学-英语语言文学] 05[文学] 

主　　题：Social Engineering Hidden Markov Model Vishing Voice Mining 

摘      要：This study examines vishing, a form of social engineering scam using voice communication to deceive individuals into revealing sensitive information or losing money. With the rise of smartphone usage, people are more susceptible to vishing attacks. The proposed Emoti-Shing model analyzes potential victims’ emotions using Hidden Markov Models to track vishing scams by examining the emotional content of phone call audio conversations. This approach aims to detect vishing scams using biological features of humans, specifically emotions, which cannot be easily masked or spoofed. Experimental results on 30 generated emotions indicate the potential for increased vishing scam detection through this approach.