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Hierarchical Identifier: Application to User Privacy Eavesdropping on Mobile Payment App

1
School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China
2
School of Cyberspace, Hangzhou Dianzi University, Hangzhou 310018, China
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(14), 3052; https://doi.org/10.3390/s19143052
Received: 6 June 2019 / Revised: 6 July 2019 / Accepted: 8 July 2019 / Published: 11 July 2019
(This article belongs to the Special Issue Threat Identification and Defence for Internet-of-Things)
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PDF [464 KB, uploaded 11 July 2019]
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Abstract

Mobile payment apps have been widely-adopted, which brings great convenience to people’s lives. However, at the same time, user’s privacy is possibly eavesdropped and maliciously exploited by attackers. In this paper, we consider a possible way for an attacker to monitor people’s privacy on a mobile payment app, where the attacker aims to identify the user’s financial transactions at the trading stage via analyzing the encrypted network traffic. To achieve this goal, a hierarchical identification system is established, which can acquire users’ privacy information in three different manners. First, it identifies the mobile payment app from traffic data, then classifies specific actions on the mobile payment app, and finally, detects the detailed steps within the action. In our proposed system, we extract reliable features from the collected traffic data generated on the mobile payment app, then use a series of well-performing ensemble learning strategies to deal with three identification tasks. Compared with prior works, the experimental results demonstrate that our proposed hierarchical identification system performs better. View Full-Text
Keywords: privacy security; mobile payment app; financial transaction action; traffic identification privacy security; mobile payment app; financial transaction action; traffic identification
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Wang, Y.; Zheng, N.; Xu, M.; Qiao, T.; Zhang, Q.; Yan, F.; Xu, J. Hierarchical Identifier: Application to User Privacy Eavesdropping on Mobile Payment App. Sensors 2019, 19, 3052.

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