A Framework for Analyzing Fraud Risk Warning and Interference Effects by Fusing Multivariate Heterogeneous Data: A Bayesian Belief Network
In the construction of a telecom-fraud risk warning and intervention-effect prediction model, how to apply multivariate heterogeneous data to the front-end prevention and management of telecommunication network fraud has become one of the focuses of this research. The Bayesian network-based fraud ri...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-06-01
|
| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/25/6/892 |
| _version_ | 1797594954341548032 |
|---|---|
| author | Mianning Hu Xin Li Mingfeng Li Rongchen Zhu Binzhou Si |
| author_facet | Mianning Hu Xin Li Mingfeng Li Rongchen Zhu Binzhou Si |
| author_sort | Mianning Hu |
| collection | DOAJ |
| description | In the construction of a telecom-fraud risk warning and intervention-effect prediction model, how to apply multivariate heterogeneous data to the front-end prevention and management of telecommunication network fraud has become one of the focuses of this research. The Bayesian network-based fraud risk warning and intervention model was designed by taking into account existing data accumulation, the related literature, and expert knowledge. The initial structure of the model was improved by utilizing City S as an application example, and a telecom-fraud analysis and warning framework was proposed by incorporating telecom-fraud mapping. After the evaluation in this paper, the model shows that age has a maximum sensitivity of 13.5% to telecom-fraud losses; anti-fraud propaganda can reduce the probability of losses above 300,000 yuan by 2%; and the overall telecom-fraud losses show that more occur in the summer and less occur in the autumn, and that the Double 11 period and other special time points are prominent. The model in this paper has good application value in the real-world field, and the analysis of the early warning framework can provide decision support for the police and the community to identify the groups, locations, and spatial and temporal environments prone to fraud, to combat propaganda and provide a timely warning to stop losses. |
| first_indexed | 2024-03-11T02:30:00Z |
| format | Article |
| id | doaj.art-b752ae4e8ad14b02ae474b8fe36062b8 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-11T02:30:00Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-b752ae4e8ad14b02ae474b8fe36062b82023-11-18T10:17:53ZengMDPI AGEntropy1099-43002023-06-0125689210.3390/e25060892A Framework for Analyzing Fraud Risk Warning and Interference Effects by Fusing Multivariate Heterogeneous Data: A Bayesian Belief NetworkMianning Hu0Xin Li1Mingfeng Li2Rongchen Zhu3Binzhou Si4School of Information and Network Security, People’s Public Security University of China, Beijing 100038, ChinaSchool of Information and Network Security, People’s Public Security University of China, Beijing 100038, ChinaSchool of Information and Network Security, People’s Public Security University of China, Beijing 100038, ChinaSchool of Information and Network Security, People’s Public Security University of China, Beijing 100038, ChinaSchool of Information and Network Security, People’s Public Security University of China, Beijing 100038, ChinaIn the construction of a telecom-fraud risk warning and intervention-effect prediction model, how to apply multivariate heterogeneous data to the front-end prevention and management of telecommunication network fraud has become one of the focuses of this research. The Bayesian network-based fraud risk warning and intervention model was designed by taking into account existing data accumulation, the related literature, and expert knowledge. The initial structure of the model was improved by utilizing City S as an application example, and a telecom-fraud analysis and warning framework was proposed by incorporating telecom-fraud mapping. After the evaluation in this paper, the model shows that age has a maximum sensitivity of 13.5% to telecom-fraud losses; anti-fraud propaganda can reduce the probability of losses above 300,000 yuan by 2%; and the overall telecom-fraud losses show that more occur in the summer and less occur in the autumn, and that the Double 11 period and other special time points are prominent. The model in this paper has good application value in the real-world field, and the analysis of the early warning framework can provide decision support for the police and the community to identify the groups, locations, and spatial and temporal environments prone to fraud, to combat propaganda and provide a timely warning to stop losses.https://www.mdpi.com/1099-4300/25/6/892telecom fraudBayesian networkearly warning frameworkmultiple heterogeneous data |
| spellingShingle | Mianning Hu Xin Li Mingfeng Li Rongchen Zhu Binzhou Si A Framework for Analyzing Fraud Risk Warning and Interference Effects by Fusing Multivariate Heterogeneous Data: A Bayesian Belief Network Entropy telecom fraud Bayesian network early warning framework multiple heterogeneous data |
| title | A Framework for Analyzing Fraud Risk Warning and Interference Effects by Fusing Multivariate Heterogeneous Data: A Bayesian Belief Network |
| title_full | A Framework for Analyzing Fraud Risk Warning and Interference Effects by Fusing Multivariate Heterogeneous Data: A Bayesian Belief Network |
| title_fullStr | A Framework for Analyzing Fraud Risk Warning and Interference Effects by Fusing Multivariate Heterogeneous Data: A Bayesian Belief Network |
| title_full_unstemmed | A Framework for Analyzing Fraud Risk Warning and Interference Effects by Fusing Multivariate Heterogeneous Data: A Bayesian Belief Network |
| title_short | A Framework for Analyzing Fraud Risk Warning and Interference Effects by Fusing Multivariate Heterogeneous Data: A Bayesian Belief Network |
| title_sort | framework for analyzing fraud risk warning and interference effects by fusing multivariate heterogeneous data a bayesian belief network |
| topic | telecom fraud Bayesian network early warning framework multiple heterogeneous data |
| url | https://www.mdpi.com/1099-4300/25/6/892 |
| work_keys_str_mv | AT mianninghu aframeworkforanalyzingfraudriskwarningandinterferenceeffectsbyfusingmultivariateheterogeneousdataabayesianbeliefnetwork AT xinli aframeworkforanalyzingfraudriskwarningandinterferenceeffectsbyfusingmultivariateheterogeneousdataabayesianbeliefnetwork AT mingfengli aframeworkforanalyzingfraudriskwarningandinterferenceeffectsbyfusingmultivariateheterogeneousdataabayesianbeliefnetwork AT rongchenzhu aframeworkforanalyzingfraudriskwarningandinterferenceeffectsbyfusingmultivariateheterogeneousdataabayesianbeliefnetwork AT binzhousi aframeworkforanalyzingfraudriskwarningandinterferenceeffectsbyfusingmultivariateheterogeneousdataabayesianbeliefnetwork AT mianninghu frameworkforanalyzingfraudriskwarningandinterferenceeffectsbyfusingmultivariateheterogeneousdataabayesianbeliefnetwork AT xinli frameworkforanalyzingfraudriskwarningandinterferenceeffectsbyfusingmultivariateheterogeneousdataabayesianbeliefnetwork AT mingfengli frameworkforanalyzingfraudriskwarningandinterferenceeffectsbyfusingmultivariateheterogeneousdataabayesianbeliefnetwork AT rongchenzhu frameworkforanalyzingfraudriskwarningandinterferenceeffectsbyfusingmultivariateheterogeneousdataabayesianbeliefnetwork AT binzhousi frameworkforanalyzingfraudriskwarningandinterferenceeffectsbyfusingmultivariateheterogeneousdataabayesianbeliefnetwork |