WCSE 2019 SUMMER ISBN: 978-981-14-1684-2
DOI: 10.18178/wcse.2019.06.082

Abnormal Detection of User Behavior in Online Banking

Yuan Wang, Liming Wang, Wei An

Abstract— Abnormal detection is very important in online banking security. One of the most difficult issues in abnormal detection is how to calculate the distance between data samples. After the analysis of user behavior of online banking, we propose a mixed method based on Euclidean distance and cosine similarity, to measure the similarity among user behaviors. This paper develops an approach to catch similar behaviors to the abnormal behaviors in online banking transactions, by using the mixed similarity measurement. Experiment results show that our method can improve the performance of abnormal detection on the underground dataset, comparing to Euclidean distance and cosine similarity.

Index Terms— Online banking; user behavior; abnormal detection

Yuan Wang, Liming Wang, Wei An
Institute of Information Engineering, Chinese Academy of Sciences, Beijing, CHINA
Yuan Wang
School of Cyber Security, University of Chinese Academy of Sciences, CHINA


Cite: Yuan Wang, Liming Wang, Wei An, "Abnormal Detection of User Behavior in Online Banking," Proceedings of 2019 the 9th International Workshop on Computer Science and Engineering, pp. 551-557, Hong Kong, 15-17 June, 2019.