Quantitative analysis of influencing factors of victimization risk of telecom network fraud driven by generative artificial intelligence

ZHOU Shengli; XU Rui; CHEN Tinggui; WANG Shaojie

doi:10.11959/j.issn.1000-0801.2025163

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Quantitative analysis of influencing factors of victimization risk of telecom network fraud driven by generative artificial intelligence

Research and Development | 更新时间：2025-08-07

- Quantitative analysis of influencing factors of victimization risk of telecom network fraud driven by generative artificial intelligence
- Telecommunications Science Vol. 41, Issue 7, Pages: 71-84(2025)
- 作者机构：
  
  1.浙江警察学院信息网络安全学院，浙江杭州 310053
  2.杭州电子科技大学网络空间安全学院，浙江杭州 310018
  3.浙江工商大学统计与数学学院，浙江杭州 310018
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2025163
  CLC： D924.3
- Received：02 April 2025，
  
  Revised：2025-07-02，
  
  Published：20 July 2025
- 稿件说明：
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周胜利,徐睿,陈庭贵等.生成式人工智能驱动下电信网络诈骗受害风险影响因素量化分析[J].电信科学,2025,41(07):71-84.

ZHOU Shengli,XU Rui,CHEN Tinggui,et al.Quantitative analysis of influencing factors of victimization risk of telecom network fraud driven by generative artificial intelligence[J].Telecommunications Science,2025,41(07):71-84.
周胜利,徐睿,陈庭贵等.生成式人工智能驱动下电信网络诈骗受害风险影响因素量化分析[J].电信科学,2025,41(07):71-84. DOI： 10.11959/j.issn.1000-0801.2025163.

ZHOU Shengli,XU Rui,CHEN Tinggui,et al.Quantitative analysis of influencing factors of victimization risk of telecom network fraud driven by generative artificial intelligence[J].Telecommunications Science,2025,41(07):71-84. DOI： 10.11959/j.issn.1000-0801.2025163.

摘要

开展生成式人工智能驱动下电信网络诈骗的受害风险影响因素研究，对于揭示犯罪规律和提升技术防治能力具有重要的理论价值与实践意义。为此，依托真实AI诈骗案件数据开展模拟实验，将犯罪过程解构为伪造信息的生成、传播与影响3个阶段，从中提取生成式人工智能、数据流、数据包、网络行为和受害风险等潜变量，再结合结构方程模型理论构建分析框架，系统量化了不同要素对受害风险的影响路径与作用贡献度。研究结果表明，生成式人工智能对受害风险具有显著的直接效应，且在整体影响效应中占据主导地位；数据流与数据包特征的中介效应较弱，在影响路径中作用不显著。

Abstract

Conducting research on the factors influencing victimization risks in generative AI (GAI) driven telecom network fraud holds significant theoretical and practical implications for areas such as summarizing patterns of criminal behavior and enhancing technological defense capabilities. For this purpose

simulation experiments were carried out based on real AI fraud case information. The criminal process was deconstructed into three stages: forged information generation

dissemination

and impact of forged information. Latent variables such as GAI

data flow

data packets

network behavior

and network risk were extracted. An analytical framework was then constructed by combining structural equation modeling theory to systematically quantify the influence paths and contribution degrees of different elements on victimization risk. The findings revealed that GAI had a significant direct effect on network risk

and the direct effect played a dominant role in the overall effect. The mediating effects of data flow and packet characteristics were weak

and its role in the influence path was not significant.

关键词

Keywords

references

刘艳红 . 网络犯罪向数字犯罪的迭代升级与刑事法应对 [J ] . 比较法研究 , 2025 ( 1 ): 1 - 15 .

LIU Y H . The evolution of cyber crime to digital crime and the response from criminal law [J ] . Journal of Comparative Law , 2025 ( 1 ): 1 - 15 .

GUPTA M , AKIRI C , ARYAL K , et al . From ChatGPT to ThreatGPT: impact of generative AI in cybersecurity and privacy [J ] . IEEE Access , 2023 , 11 : 80218 - 80245 .

GRESSEL G , PANKAJAKSHAN R , MIRSKY Y . Discussion paper: exploiting LLMs for scam automation: a looming threat [C ] // Proceedings of the 3rd ACM Workshop on the Security Implications of Deepfakes and Cheapfakes . New York : ACM Press , 2024 : 20 - 24 .

WU T Y , HE S Z , LIU J P , et al . A brief overview of ChatGPT: the history, status quo and potential future development [J ] . IEEE/CAA Journal of Automatica Sinica , 2023 , 10 ( 5 ): 1122 - 1136 .

陈德良 , 王火剑 , 赵加俊 . 电信网络诈骗犯罪现状分析与治理对策研究: 以浙江省为例 [J ] . 浙江警察学院学报 , 2023 ( 6 ): 67 - 73 .

CHEN D L , WANG H J , ZHAO J J . Research on the current status analysis and the countermeasures of telecom and Internet fraud: taking Zhejiang Province as an example [J ] . Journal of Zhejiang Police College , 2023 ( 6 ): 67 - 73 .

DELIEMA M . Elder fraud and financial exploitation: application of routine activity theory [J ] . The Gerontologist , 2018 , 58 ( 4 ): 706 - 718 .

刘晓倩 . 电信诈骗受害者的特征分析与预防策略 [J ] . 法制与社会 , 2021 ( 7 ): 140 - 141 .

LIU X Q . Characteristics analysis and preventive strategies of telecom fraud victims [J ] . Legal System and Society , 2021 ( 7 ): 140 - 141 .

刘晓萌 . 电信诈骗年轻化趋势: 受害者心理分析与防范策略 [J ] . 西部学刊 , 2024 ( 24 ): 64 - 67 .

LIU X M . The trend of younger victims in telecommunication fraud: psychological analysis of victims and prevention strategies [J ] . Journal of Western , 2024 ( 24 ): 64 - 67 .

田丽娟 , 钱虹 . 电信诈骗事件中大学生受害者的心理特征分析及防范路径 [J ] . 西部学刊 , 2023 ( 11 ): 131 - 134 .

TIAN L J , QIAN H . Analysis of psychological characteristics of college students' victims in telecom fraud and its prevention path [J ] . Journal of Western , 2023 ( 11 ): 131 - 134 .

刘鑫悦 , 范超云 , 李辉 . 电信网络诈骗被害人群体特征及防范对策 [J ] . 云南警官学院学报 , 2022 ( 4 ): 111 - 122 .

LIU X Y , FAN C Y , LI H . Characteristics and preventive countermeasures of telecom and network fraud victims [J ] . The Journal of Yunnan Police College , 2022 ( 4 ): 111 - 122 .

柳林 , 吴林琳 , 张春霞 , 等 . 接触型与非接触型犯罪时空稳定性对比及其联合防控: 以盗窃和电信网络诈骗为例 [J ] . 地理研究 , 2022 , 41 ( 11 ): 2851 - 2865 .

LIU L , WU L L , ZHANG C X , et al . Comparison of spatio-temporal stability between contact crime and non-contact crime and their joint prevention and control: a study of theft and telecommunication network fraud [J ] . Geographical Research , 2022 , 41 ( 11 ): 2851 - 2865 .

张帆锐 , 石拓 , 尤慧 . 电信网络诈骗被害人群空间统计分布及风险特征研究:以刷单返利类为例 [J ] . 调研世界 , 2024 : 1 - 9 .

ZHANG F R , SHI T , YOU H . Research on the spatial statistical distribution and risk characteristics of the telecommunications fraud victims: take for example the category of rebates on brush orders [J ] . The World of Survey and Research , 2024 : 1 - 9 .

董安阳 , 胡晓光 . 我国电信网络诈骗犯罪的时空分布及社会人口特征 [J ] . 江苏警官学院学报 , 2024 , 39 ( 1 ): 109 - 115 .

DONG A Y , HU X G . Analysis of spatio-temporal characteristics and socio-demographic characteristics of telecom network fraud crime [J ] . Journal of Jiangsu Police Institute , 2024 , 39 ( 1 ): 109 - 115 .

NI P F , YU W . A victim-based framework for telecom fraud analysis: a Bayesian network model [J ] . Computational Intelligence and Neuroscience , 2022 , 2022 ( 1 ): 7937355 .

DAS R , AHMED W , SHARMA K , et al . Towards the development of an explainable e-commerce fake review index: an attribute analytics approach [J ] . European Journal of Operational Research , 2024 , 317 ( 2 ): 382 - 400 .

GUO Z Y . Online disinformation and generative language models: motivations, challenges, and mitigations [C ] // Proceedings of the Companion Proceedings of the ACM Web Conference 2024 . New York : ACM Press , 2024 : 1174 - 1177 .

FAGNI T , FALCHI F , GAMBINI M , et al . TweepFake: about detecting deepfake tweets [J ] . PLoS One , 2021 , 16 ( 5 ): e0251415 .

AYOOBI N , SHAHRIAR S , MUKHERJEE A . The looming threat of fake and LLM-generated LinkedIn profiles: challenges and opportunities for detection and prevention [C ] // Proceedings of the 34th ACM Conference on Hypertext and Social Media . New York : ACM Press , 2023 : 1 - 10 .

毛太田 , 汤淦 , 马家伟 , 等 . 人工智能生成内容（AIGC）用户采纳意愿影响因素识别研究: 以ChatGPT为例 [J ] . 情报科学 , 2024 , 42 ( 7 ): 126 - 136 .

MAO T T , TANG G , MA J W , et al . Factors influencing user adoption intention of artificial intelligence generated content(AIGC): a study on ChatGPT [J ] . Information Science , 2024 , 42 ( 7 ): 126 - 136 .

钱洪伟 , 王旭 , 高宁 . 生成式人工智能ChatGPT风险形成机理与防范策略研究 [J ] . 中国应急管理科学 , 2024 ( 11 ): 112 - 122 .

QIAN H W , WANG X , GAO N . Research on the formation mechanism and prevention strategies of risks in generative artificial intelligence ChatGPT [J ] . Journal of China Emergency Management Science , 2024 ( 11 ): 112 - 122 .

刘仁文 . 生成式人工智能财产犯罪的特点与应对 [J ] . 国家检察官学院学报 , 2025 , 33 ( 2 ): 10 - 14 .

LIU R W . Characteristics and responses to generative artificial intelligence property crimes [J ] . Journal of National Prosecutors College , 2025 , 33 ( 2 ): 10 - 14 .

蔡梦虹 . 直播带货情境下AI虚拟主播对消费者冲动购买行为的影响: 基于技术可供性视角 [J ] . 商业经济研究 , 2024 ( 23 ): 81 - 84 .

CAI M H . The influence of AI virtual anchor on consumers' impulse buying behavior in live broadcasting with goods: based on the perspective of technical availability [J ] . Journal of Commercial Economics , 2024 ( 23 ): 81 - 84 .

胡剑 , 戚湧 . 开源创新社区用户知识共享行为影响因素研究: 基于SEM与fsQCA的实证分析 [J ] . 情报科学 , 2023 , 41 ( 9 ): 59 - 68, 77 .

HU J , QI Y . The influencing factors of users' knowledge sharing behavior in the open-source innovation community: an empirical analysis based on SEM and fsQCA [J ] . Information Science , 2023 , 41 ( 9 ): 59 - 68, 77 .

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