E-commerce fraud risk prediction based on RUSBoost algorithm

Xinyan Liu; Shancheng Lin; Hongyu Lv; Xiao Ruan; Ning Ding

doi:10.1117/12.2634712

4 May 2022 E-commerce fraud risk prediction based on RUSBoost algorithm

Xinyan Liu, Shancheng Lin, Hongyu Lv, Xiao Ruan, Ning Ding

Proceedings Volume 12172, International Conference on Electronic Information Engineering and Computer Communication (EIECC 2021); 121721A (2022) https://doi.org/10.1117/12.2634712
Event: International Conference on Electronic Information Engineering and Computer Communication (EIECC 2021), 2021, Nanchang, China

Abstract

In the context of the era of big data, the emergence of e-commerce platforms has brought many opportunities and risks. Due to the COVID-19, e-commerce has achieved unprecedented development, and e-commerce fraud has severely damaged the healthy economic environment. This paper uses the RUSBoost algorithm to build an e-commerce fraud risk prediction model, and verifies the predictive performance of the model through data experiments. The results show that it has a high accuracy rate for identifying e-commerce fraud. If the model is applied to e-commerce, the losses caused by ecommerce fraud could be avoided in time. At present, there are fewer e-commerce fraud risk prediction models and have a wide development prospection.

Citation Download Citation

Xinyan Liu, Shancheng Lin, Hongyu Lv, Xiao Ruan, and Ning Ding "E-commerce fraud risk prediction based on RUSBoost algorithm", Proc. SPIE 12172, International Conference on Electronic Information Engineering and Computer Communication (EIECC 2021), 121721A (4 May 2022); https://doi.org/10.1117/12.2634712

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