Summary
Voice
mail technology has its demerits the biggest of which is lack of privacy. As
more and more people continue to use the system, the threat continues to grow
daily. This paper suggests a voice privacy system which would guarantee
privacy. The system will not only optimize the bandwidth but also enhance
privacy in sensitive organizations like banks
Statement
of the problem
Each
time you use the telephone or the voice mail, you are risking being overhead by
an eavesdropper. While the implications may not be too high for the home use,
the case is different for the business environment like the bank. We have
already heard of sensitive information being lost due to eavesdropping on phone
calls between business magnates that have resulted in huge losses or scandals.
Solution
While using of the telephone to make
business transactions results into security loopholes, the proposed model has a
solution to this. It makes it possible to have privacy guaranteed. The model is
built on the foundation of wavelets. The model is able to transform sound at
the sending node and the receiving node will recover the sound by making an
inverse transformation. It uses the mechanism of Discrete Wavelet
Transformation (DWT) to achieve this (Poliker).
Background
Traditionally,
privacy of systems was considered to be a military prerequisite. The concept of privacy in the commercial
systems developed much later. Voice mail is a product that is provided by many
vendors and adding a form of privacy to it would make it even more palatable.
The telecommunication industry is suffering great losses due issues related to
eavesdropping.
Methods
Wavelet analysis is done by breaking
down of the signal into segments (wavelets). The wavelet has very irregular
shapes and they are also compactly supported. This is desirable qualities in analyzing
of signals that are not stationary. The irregular nature of the wavelets makes
it possible for them to analyze a signal that is discontinuous and one which
has acute changes. The feature of compactly supported allows the wavelet makes
it possible to localize signal features.
The main idea in the proposed model is
doing away with the irregular transformation. Instead the model will use
discrete wavelet transformation (DWT). This will result in five dissimilar
bandwidths of frequencies 0-250, 250-500, 500-1000, 1000-2000, 2000-40000.
Since the normal telephone sound rarely exceed 2000, the 2000-4000 band is discarded.
We will take an arbitrary block sample of 32 (which can be increased to achieve
higher security). The speech is
synthesized and translated by 250mz. On the receiving node, the speech converted
back to the original band (0-2000). The sound is then read by the MATLAB
application. MATLAB is universally used for processing of digital data (Stormy, 147). The figure below summarizes the process both on
the sending and the receiving nodes.
Sending
node
Receiving
node
shecheduling
January 10 January
15 February
2
initial prepation installation of system testing of
system Job completion
The suggested budget is as follows:-
Purchase of equipment(cabling,
Convertor, tonegenerators) 500,000
Outsourcing costs 10,000
labor costs 6,700
total 516,700
Conclusion
The proposed model will go along way in
securing telephone transaction for the bank and will therefore seal the
loophole that exists which could otherwise be used as a channel for
eavesdropping and lead to fraudulent activity. Once implemented, the model can
be adopted by other organizations including the military to secure
communications across the telephone lines.
Works
Cited
Poliker Robi. The wavelet Tutorial. 12th
January 2001. 14th November, 2010. <http://users.rowan.edu/~polikar/WAVELETS/WTtutorial.html>
Stormy
Attaway. MATLAB: a practical introduction to
programming and problem solving. London, Butterworth-Heinemann, 2009.
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