Research Article
EMCV: Enhancing the Security of the Mobile Commerce using Voice Features
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 44 - Issue 16 |
| Published: April 2012 |
| Authors: Sonal Gupta |
10.5120/6350-8702
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Sonal Gupta . EMCV: Enhancing the Security of the Mobile Commerce using Voice Features. International Journal of Computer Applications. 44, 16 (April 2012), 38-41. DOI=10.5120/6350-8702
@article{ 10.5120/6350-8702,
author = { Sonal Gupta },
title = { EMCV: Enhancing the Security of the Mobile Commerce using Voice Features },
journal = { International Journal of Computer Applications },
year = { 2012 },
volume = { 44 },
number = { 16 },
pages = { 38-41 },
doi = { 10.5120/6350-8702 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2012
%A Sonal Gupta
%T EMCV: Enhancing the Security of the Mobile Commerce using Voice Features%T
%J International Journal of Computer Applications
%V 44
%N 16
%P 38-41
%R 10.5120/6350-8702
%I Foundation of Computer Science (FCS), NY, USA
Abstract
M-Commerce is an emerging market. As with any emerging market there are some significant opportunities and risks . In M-Commerce security risk is major risk which this proposed system will try to remove . The most important element of M-Commerce is security issues and how this proposed system can make it safe for customers to feel comfortable while using mobile phones. Biometric authentication technology is best to resolve security issues related to M-Commerce as this will provide one's uniqueness. In the proposed system M-Commerce Web Page is created in PHP which will then integrate with Matlab. Start by taking input speech through microphone whose voice need to be authenticated. Then features will be extract from voice through combined use of algorithms Linear Prediction Coding (LPC), and Mel-Frequency Cepstrum Coefficients (MFCC) to increase reliability and recognition quality. After feature extraction, matching of those features will be done through both algorithms Hidden Markov Modeling (HMM) and Vector Quantization (VQ) separately. At most one feature should be matched from both algorithms separately then only authenticated person will get login through Web Page.
References
- Gong Chen (2010) " Security System based on Speech Recognition in Mobile Commerce",School Of Information Science and Engineering Southeast University Nanjing, China .
- Jiehua Dai, Zhengzhe Wei(2007) "Study and Implementation of Feature Extraction and Comparison in Voice Recognition".
- John Garofalakis,Flora (2008)"System's Design and implementation for easy creation of M-Commerce Systems" ,Flora Garofalakis,Vasilios Stefanis
- Mahmoud I. Abdalla and Hanaa S. Ali (2010) "Wavelet-Based Mel-Frequency Cepstral Coefficients for Speaker Identification using Hidden Markov Models". JOURNAL OF TELECOMMUNICATIONS, VOLUME 1, ISSUE 2, MARCH 2010.
- Qiong Long(2011) "A Construction Strategy Framework For M-Commerce Websites" Business School Beijing Institute of Fashion Technology Beijing, China
- Rajeev Aggarwal(2011)" Noise Reduction of Speech Signal using Wavelet Transform with Modified Universal Threshold". International Journal of Computer Applications (0975 – 8887) Volume 20– No. 5, April 2011.
- Rashad Yazdanifard ,Mohamed Sayed (2011) " M-Commerce and Related Mobile Security Issues", Faculty of Management, Multimedia University Technology, Cyberjaya, Malaysia.
- Yi Lei, Bingyong and Jin Lice(2011) " Evaluation of communication platform in E-Commerce and M-Commerce",Economic and management School NanChang Hangkong University Sponsor JiangXi Province Education and Science "12th five year plan"
- Jiehua Dai, Zhengzhe Wei(2007) "Study and Implementation of Feature Extraction and Comparison in Voice Recognition". A project report
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