Open AccessMobile payment anomaly detection mechanism based on information entropy
Author(s) -
Zhang Zhenjiang,
Wang Xiaoni,
Sun Lin
Publication year - 2016
Publication title -
iet networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.466
H-Index - 21
ISSN - 2047-4962
DOI - 10.1049/iet-net.2014.0101
Subject(s) - anomaly detection , payment , entropy (arrow of time) , mechanism (biology) , computer science , anomaly (physics) , data mining , world wide web , physics , quantum mechanics , condensed matter physics
With the rapid growth in the number of mobile phone users, mobile payments have become an important part of mobile e‐commerce applications. Secure payment systems directly affect the security of e‐commerce systems. This study proposes an anomaly detection mechanism supported by an information entropy method combined with neural network to improve mobile payments security. As the entropy value is sensitive and have much difference between normal and abnormal traffic flow in the mobile payment system, the abnormal traffic data will be detected. The simulation result shows that it can realise the effective monitoring of abnormal flow in the mobile payment system.