Design and Implementation of a Malware Detection System for Mobile Payment on the Cloud

doi:10.3969/j.issn.1671-1122.2016.01.011

Abstract

Abstract:

More and more users choose to use mobile terminals for payment. But at the same time, mobile payment security risks are becoming increasingly prominent. In this paper, based on the analysis of a variety of payment threats users faced, we propose a malware detection system for mobile payment on cloud platform. We use the method of combining cloud terminal with the mobile, and simulate the mobile payment through simulator in the cloud to test the sensitive behaviors before APP running, output and parse operation logs, and judge whether it has malicious behavior through the custom rules , which can detect the malicious software before malicious behaviors happen. We also accompany the function of silently installing testing to prevent sub-package silently installing in mobile phone background to escape system testing, which can protect users’ mobile payment security more comprehensively and effectively. Finally, the experiments prove effectiveness and practicability of this system.

Key words: mobile payments, secondary packaging, malware detection, cloud platform

CLC Number:

TP309

Yaqian SHU, Anmin FU, Zhentao HUANG. Design and Implementation of a Malware Detection System for Mobile Payment on the Cloud[J]. Netinfo Security, 2016, 16(1): 59-63.

Figures/Tables 7

References 13

[1]	姬炳帅,李虎,韩伟红,等. 面向电子商务的用户异常行为检测研究[J]. 信息网络安全,2014(9):80-85.
[2]	文伟平, 梅瑞, 宁戈,等. Android恶意软件检测技术分析和应用研究[J]. 通信学报,2014,35(8):78-85.
[3]	BATYUK L, HERPICH M, Camtepe S A, et al.Using Static Analysis for Automatic Assessment and Mitigation of Unwanted and Malicious Activities within Android Applications[C]//IEEE Computer Society. IEEE 6th International Conference on Malicious and Unwanted Software, October18-19, 2011,Fajardo, Puerto Rico,USA.Piscataway, NJ: IEEE. 2011: 18-19.
[4]	赵洋,胡龙,熊虎,等.基于沙盒的Android恶意软件动态分析方案[J]. 信息网络安全,2014(12):21-26.
[5]	BURGUERA I, ZURUTUZA U, Nadjm-Tehrani S.Crowdroid: Behavior-based Malware Detection System for Android[C]//ACM. Proceedings of the 1st ACM workshop on Security and privacy in smartphones and mobile devices, Octobor 17-21, 2011, Chicago, Illinois, USA. New York: ACM, 2011:15-26.
[6]	王丽娜, 谈诚, 陈栋,等. Android系统中基于移动支付行为特征的恶意检测研究与实现[EB/OL]. .
[7]	FUN T S, BENG L Y, LIKOH J, et al.A Lightweight and Private Mobile Payment Protocol by Using Mobile Network Operator[C]// IEEE Computer Society. IEEE International Conference on Computer and Communication Engineering,May 13-15, 2008, International Islamic University, Kuala Lumpur,Malaysia. Piscataway, NJ: IEEE, 2008: 162-166.
[8]	ZHOU Y, JIANG X.Dissecting Android Malware: Characterization and Evolution[C]// IEEE Computer Society. IEEE Symposium on Security and Privacy, May 20-23, 2012, San Francisco,California,USA. Piscataway, NJ: IEEE,2012: 95-109.
[9]	兰芸,李宝林. 木马恶意软件的电子数据勘查与取证分析初探[J]. 信息网络安全,2014(5):87-91.
[10]	REHMAN S U, Abid M.An Empirical Research on the User Acceptance of Mobile Payment System[C]//IEEE Computer Society. IEEE International Conference on Information Society, November 10-12, 2014, London,United Kingdom.Piscataway, NJ: IEEE, 2014: 329-335.
[11]	JACOB G, DEBAR H, FILIOL E.Behavioral Detection of Malware: from a Survey towards an Established Taxonomy[J]. Journal in Computer Virology, 2008, 4(3): 251-266.
[12]	ZHOU T.An Empirical Examination of Initial Trust in Mobile Payment[J]. Wireless Personal Communications, 2014, 77(2): 1519-1531.
[13]	胡文君, 赵双, 陶敬,等. 一种针对Android平台恶意代码的检测方法及系统实现[J]. 西安交通大学学报,2013,47(10):37-43.