An identification method of digital economy security risk dimension based on Bayesian network Online publication date: Thu, 08-Feb-2024
by Rong Xia; Xueqin Ni
International Journal of Sustainable Development (IJSD), Vol. 27, No. 1/2, 2024
Abstract: In order to improve the recall rate and accuracy rate of digital economy security risk identification and reduce the identification time, this paper proposes a Bayesian network based risk dimension identification method for digital economy security. Firstly, the principle of establishing an evaluation indicator system is to screen risk indicators through the boundary value method to obtain a risk indicator system; then, K-means clustering is used to classify the risk levels and construct a risk identification function; finally, Bayesian network learning is used to solve the identification function and achieve the identification of security risk dimensions. The results show that the recall rate under this method is always higher than 98%, the accuracy of risk dimension identification is always higher than 93%, and the time required for risk dimension identification does not exceed 5.0 seconds, indicating that this method can effectively improve the effectiveness of risk dimension identification.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Sustainable Development (IJSD):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook