Mobile payment anomaly detection mechanism based on information entropy. Issue 1 (1st January 2016)

• Record Type: Journal Article
• Authors: Zhang, Zhenjiang; Wang, Xiaoni; Sun, Lin
• Is Part Of: IET networks. Volume 5:Issue 1(2016)
• Page Start: 1
• Page End: 7
• Publication Date: 2016-01-01
• Subjects: mobile commerce -- entropy -- telecommunication traffic -- IP networks -- computer network security; mobile payment system anomaly detection mechanism -- mobile phone users -- mobile e‐commerce applications -- e‐commerce system security -- information entropy method -- neural network -- mobile payment security improvement -- sensitive entropy value -- normal traffic flow monitoring -- abnormal traffic flow monitoring -- abnormal traffic data detection; Computer network architectures -- Periodicals; Computer network protocols -- Periodicals; Information networks -- Periodicals; Telecommunication systems -- Periodicals; 004.605
• DOI: 10.1049/iet-net.2014.0101
• Languages: English
• ISSNs: 2047-4954

Abstract

Abstract : 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.