Research on evaluation of network payment security
by Xiang Xie; Yingte Wang; Ying Cui
International Journal of Information Technology and Management (IJITM), Vol. 22, No. 1/2, 2023

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.

Online publication date: Wed, 05-Apr-2023

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