Secure e-Trading With Your Voice!!!

The development of information and communication technology  (ICT) is rapidly changing human lifestyle. Now, human can do many activities especially finance-related activities such as banking or trading (e-commerce, e-trading and e-banking) by using internet. It is absolutely ease human activity but in other side, it will endanger their private data from the impostor or eavesdropper over network. Consequence of this problem is the need of higher level of verification security.

However, the provider of online finance-related activity still uses conventional methods such as PIN number and password although this verification method is very mature from the cyber crime attacks such as hacking, cracking and carding. Therefore, we need higher secure verification method to secure private data of users and biometric system can be a solution in this problem.

Biometric is identification method  using human physical identity of user such as face, voiceprint, gait, etc. This method is more reliable than conventional one because its characteristics or feature is specific for each human. Moreover, this biometric cannot easily imitated by others who are not legitimate.

We implement voice biometric using unique feature of voice as human identity in the web login page. Instead of its security consideration, voice biometric is the most feasible biometric to be used in the internet application because the microphone is the standard equipment for online activity so user does not need the other equipment anymore.

This system is built using 14 MFCC coefficients, 12 mixtures of GMM and Secure Socket Layer with RSA 1024 Bit encryption for network security.

This research result will be beneficial for e-commerce/e-trading and e-banking application which need very high security tool for their customer account.

You can get the paper by request by email me at budiman.fgi@gmail.com.

Source:

B. Putra, Suyanto, “Implementation of Secure Speaker Verification at Web Login Page Using Mel Frequency Cepstral Coefficient-Gaussian Mixture Model (MFCC-GMM)”,  Proceeding of International Conference on Instrumentation, Control and Automation (ICA 2011), Institut Teknologi Bandung, Bandung, Indonesia, 2011. Published on IEEE Xplore with ISBN:978-1-4577-1461-0, IEEE Catalog Number: CFP1179P-ART.  [Available]: http://ieeexplore.ieee.org