Deep feature representation for anti-fraud system

摘要

Online payment is becoming popular due to the development of e-commerce. So payment safety is more important. Since there is a fraudulent situation, an anti-fraud system is indispensable. GMM was lever-aged in many anti-fraud applications, but it only takes positive sample into account. Convolutional neural network is a strong strategy for learning deep representation of samples. So in this paper, we propose a CNNs architecture to deal with this problem. And the distance metric method can effectively identify whether candidates are the same person. Experimental results show the effectiveness of our method. (C) 2019 Published by Elsevier Inc.