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Research Article

Legal system-oriented telecom fraud detection, identification and prevention

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  • @ARTICLE{10.4108/eetsis.3335,
        author={Zhaoling Liu},
        title={Legal system-oriented telecom fraud detection, identification and prevention},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={10},
        number={6},
        publisher={EAI},
        journal_a={SIS},
        year={2023},
        month={9},
        keywords={legal system, telecom fraud, boosting algorithm, CatBoost, accuracy},
        doi={10.4108/eetsis.3335}
    }
    
  • Zhaoling Liu
    Year: 2023
    Legal system-oriented telecom fraud detection, identification and prevention
    SIS
    EAI
    DOI: 10.4108/eetsis.3335
Zhaoling Liu1,*
  • 1: Hebei Finance University
*Contact email: izl617278@163.com

Abstract

INTRODUCTION: With the development of technology, telecom fraud is appearing more and more frequently and causing more and more harm. OBJECTIVES: This paper focused on the detection, identification, and prevention of telecom fraud. METHODS: Firstly, the telecom fraud crime was analyzed, the existing legal system was explained, and some suggestions on the protection of telecom fraud were proposed at the legal level. Then, the characteristics of telecom fraud users were analyzed to point out the differences between fraud users and normal users in terms of call, message, and traffic behavior. Finally, the Boosting algorithm was used to detect and identify telecom fraud. RESULTS: The experiments found that the boosting algorithm had advantages in the detection and recognition of telecom fraud compared with the algorithms such as support vector machine and random forest algorithms. Among several boosting algorithms, the CatBoost algorithm performed the best, with an accuracy of 0.9465 and an F1 value of 0.9047. CONCLUSION: The results demonstrate the reliability of the CatBoost algorithm in detecting and recognizing telecom fraud, and it can be applied in practice.

Keywords
legal system, telecom fraud, boosting algorithm, CatBoost, accuracy
Received
2023-05-12
Accepted
2023-09-15
Published
2023-09-18
Publisher
EAI
http://dx.doi.org/10.4108/eetsis.3335

Copyright © 2023 Z. L. Liu, licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

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