Authors: Xiang Xie; Yingte Wang; Ying Cui
Addresses: School of Economics and Management, Beijing Jiaotong University, No. 3 ShangYuanCun, Beijing 100044, China ' School of Economics and Management, Beijing Jiaotong University, No. 3 ShangYuanCun, Beijing 100044, China ' School of Economics and Management, Beijing Jiaotong University, No. 3 ShangYuanCun, Beijing 100044, China
Abstract: This paper collects data about network payment fraud through a questionnaire and then analyses the data. We propose a prediction model based on the hybrid support degree apriori algorithm. First, is to find out the factors that are closely related to the success of cheating. Then, we find for the nodes of the decision tree and their importance by using the ID3 algorithm to construct the decision tree. We then construct and verify the evaluation index system of the network payment from the user's point of view while considering the results of association rules and decision tree, and combined with principal component analysis and text mining results. Finally, we determine the weight using entropy method. With the proposed model, we can determine the probability of being deceived according to the situation of different people. This not only reminds people to be vigilant but also provides a reference for the community.
Keywords: apriori algorithm; ID3 algorithm; internet payment security; styling; evaluation system; principal component analysis; entropy method.
International Journal of Information Technology and Management, 2023 Vol.22 No.1/2, pp.110 - 126
Accepted: 30 Mar 2019
Published online: 05 Apr 2023 *