<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The security assessment of corporate financial systems has become a popular area of research, although few results have been published so far. This research focuses on integrating the association rule algorithm with Bayesian networks to evaluate the security of corporate financial systems. It primarily employs Bayesian networks to calculate the conditional probability, prior joint probability, and posterior probability of each attribute node in the IDRI-Tree to assess the security of the company’s financial system. Additionally, abnormal data from Company A’s financial system were collected to evaluate the method’s effectiveness. The results indicate that Company A’s financial system has data discrepancy compliance rates of 98.92% and 96.50%, respectively. The security assessment scores for monitoring, evaluation, and assessment in financial system security are the lowest, averaging 1.41, while the scores for payment, service, and support are the highest, averaging 3.32. The financial system security assessment method proposed in this paper demonstrates high practical value and offers a reference for the future establishment and improvement of financial system security assessment methods.</p>
</abstract>

The security assessment of corporate financial systems has become a popular area of research, although few results have been published so far. This research focuses on integrating the association rule algorithm with Bayesian networks to evaluate the security of corporate financial systems. It primarily employs Bayesian networks to calculate the conditional probability, prior joint probability, and posterior probability of each attribute node in the IDRI-Tree to assess the security of the company’s financial system. Additionally, abnormal data from Company A’s financial system were collected to evaluate the method’s effectiveness. The results indicate that Company A’s financial system has data discrepancy compliance rates of 98.92% and 96.50%, respectively. The security assessment scores for monitoring, evaluation, and assessment in financial system security are the lowest, averaging 1.41, while the scores for payment, service, and support are the highest, averaging 3.32. The financial system security assessment method proposed in this paper demonstrates high practical value and offers a reference for the future establishment and improvement of financial system security assessment methods.

A Security Assessment Strategy for Corporate Financial Systems Based on Data Mining Techniques

Taiyuan tourism college-Department of Information Management

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

The security assessment of corporate financial systems has become a popular area of research, although few results have been published so far. This research...

A Security Assessment Strategy for Corporate Financial Systems Based on Data Mining Techniques

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 11. Apr. 2024

Akzeptiert: 09. Juli 2024

DOI: https://doi.org/10.2478/amns-2024-1880

Schlüsselwörter
Data mining, Association rules, IDRI-Tree tree, Bayesian network, Security assessment

© 2024 Jianhong Wu., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

A Security Assessment Strategy for Corporate Financial Systems Based on Data Mining Techniques

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 11. Apr. 2024

Akzeptiert: 09. Juli 2024

DOI: https://doi.org/10.2478/amns-2024-1880

SchlüsselwörterData mining, Association rules, IDRI-Tree tree, Bayesian network, Security assessment

© 2024 Jianhong Wu., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Data mining, Association rules, IDRI-Tree tree, Bayesian network, Security assessment