Title
ReMEMBeR: Ranking Metric Embedding-Based Multicontextual Behavior Profiling for Online Banking Fraud Detection
Abstract
Anomaly detection relies on individuals’ behavior profiling and works by detecting any deviation from the norm. When used for online banking fraud detection, however, it mainly suffers from three disadvantages. First, for an individual, the historical behavior data are often too limited to profile his/her behavior pattern. Second, due to the heterogeneous nature of transaction data, there lacks a ...
Year
DOI
Venue
2021
10.1109/TCSS.2021.3052950
IEEE Transactions on Computational Social Systems
Keywords
DocType
Volume
Online banking,Anomaly detection,Measurement,Credit cards,Collaboration,Radio frequency,Data models
Journal
8
Issue
ISSN
Citations 
3
2329-924X
1
PageRank 
References 
Authors
0.39
0
3
Name
Order
Citations
PageRank
Jipeng Cui110.39
Chun-Gang Yan26215.97
Cheng Wang35811.05