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Updated: Aug 29, 2025

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
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A Victim-Based Framework for Telecom Fraud Analysis: A Bayesian Network Model.

Peifeng Ni1, Wei Yu2

  • 1School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China.

Computational Intelligence and Neuroscience
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Summary

This study introduces a Bayesian network (BN) model for predicting telecom fraud victims. It identifies specific demographics, like government male staff and female students, as most vulnerable to certain fraud types, aiding proactive prevention strategies.

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Area of Science:

  • Cybersecurity
  • Criminology
  • Data Science

Background:

  • Telecom fraud poses a significant threat to public safety.
  • Prevention strategies are shifting from reactive to proactive measures.
  • Understanding victim characteristics is crucial for effective intervention.

Purpose of the Study:

  • To develop a victim analysis and prediction method for telecom fraud.
  • To model victim demographics and their relationship to fraud outcomes.
  • To provide decision support for law enforcement and community prevention.

Main Methods:

  • Utilized a Bayesian network (BN) model to analyze victim data.
  • Incorporated factors such as age, gender, occupation, and education level.
  • Learned BN parameters using 533 real telecom fraud cases and expert experience.

Main Results:

  • Identified specific high-risk victim profiles: males in government for shopping fraud, females in schools for phishing/virus fraud.
  • Quantified uncertainty and complex relationships among influencing factors.
  • Determined that victim characteristics have minimal impact on reporting fraud to the police.

Conclusions:

  • The BN model effectively analyzes victim characteristics to predict fraud vulnerability and property loss.
  • Findings support targeted prevention efforts based on demographic profiles.
  • The model offers valuable decision support for combating telecom fraud.