Application and Optimization of Algorithm Technology in the Criminal Governance of Telecom Network Fraud from the Perspective of Data Governance

DOI: https://doi.org/10.62517/jbdc.202501105

Author(s)

Jiazhi Yu

Affiliation(s)

Department of Public Security Management, Beijing Police College, Beijing, China

Abstract

As we witness the swift progression of information technology, the issue of telecom network fraud has become increasingly prevalent, posing a significant threat to the well-being of society. Consequently, the prevention of such fraudulent activities has become an urgent matter that requires immediate attention. In this contemporary era, the advancement of algorithm technology in managing telecom network fraud has opened up new avenues and methodologies, offering support to entities combating fraud by enhancing the efficiency of their operations and refining the precision of their preventative measures. However, during the implementation of algorithm technology, the issue of data governance has surfaced and become a topic of public concern. Hence, this paper delves into the analysis of algorithm application and optimization from the perspective of data governance, exploring the synergistic effects of these two elements in the fight against telecom network fraud crimes. The goal is to offer insights that can contribute to enhancing the overall effectiveness of fraud governance strategies.

Keywords

Data Governance Algorithm Technology Telecom; Network; Fraud; Fraud Governance; Governance Effect

References

[1]Wei Wei, Shang Tieli, Zhou Shuai. The influence of artificial intelligence on the management of telecom network fraud and its coping ideas. Information and communication Technology and Policy, 2020, (04): 80-84. [2]Wu Dan. Under the background of artificial intelligence, telecom and network fraud crime pattern and digital governance. Public Security Research, 2024, (10): 87-97. [3]Kou Jianbo. Artificial intelligence policing ethics from a people-oriented perspective. Journal of the People's Police University of China, 2023, 39 (04): 31-40. [4]Zheng Zhihang. Ethical crisis and legal regulation of artificial intelligence algorithm. Social Science Digest, 2021, (04): 74-76. [5][Kafhali E S, Tayebi M, Sulimani H. An Optimized Deep Learning Approach for Detecting Fraudulent Transactions. Information, 2024, 15(4):227-. [6]Gianluca Gabrielli, et al. "The power of big data affordances to reshape anti-fraud strategies." Technological Forecasting & Social Change 205. (2024):123507-. [7]Thunderstorm Xin, Ai Zhiqiang. Control and governance: algorithmic technical risk and its response. Journal of Liaoning Polytechnic University (Social Science Edition), 2024, 26(03):5-7. DOI:10. 15916/j.issn1674-327x. 2024.03. 002. [8]Yang Shengqin. The influence of AI on the criminal governance of telecom network fraud from ChatGPT. Research on Crime and Transformation, 2024, (05): 26-33. [9]Yang Huan. Application of artificial intelligence technology and risk regulation in police work. Journal of Liaoning Police College, 2024, 26 (01): 83-88. [10]Wei Wei, Shang Tieli, Zhou Shuai. The influence of artificial intelligence on the management of telecom network fraud and its coping ideas. Information and communication Technology and Policy, 2020, (04): 80-84. [11]Zhang Aijun and Wang Hang, Algorithm: A New Form of Power, Research on Governance Modernization, no. 1, 2020 [12]Zhang Aijun, Li Feng, Algorithm Power in the Era of Artificial Intelligence: Logic, Risk and Regulation, Journal of Hohai University (Philosophy and Social Sciences Edition), no. 6, 2019 [13]Xin Zhang. From algorithmic crisis to algorithmic trust: multiple solutions and localization path of algorithmic governance. Journal of East China University of Political Science and Law, 2019, 22 (06): 17-30.