Dr. Nidaa A. Abbas, Member, IEEEdrnidaa_muhsin@ieee.org 

 
Abstract:

 
Scrambling methods are considered as important methods that provide the communication systems a specified degree of security, depending on the used technique to implement the scrambling method. There are many traditional scrambling methods used in single dimension such as time or frequency domain scrambling. This paper proposes the application of analog speech scrambler (also called analog speech encryption) using statistical method called Principal Component Analysis (PCA). Practically the descrambling process is implemented using traditional PCA algorithm and taking into consideration the test cases of many input speech signals. The objective test using Linear Predictive Coding (LPC) and Signal-to-Noise Ratio (SNR) where applied to evaluate the proposed system. It is shown via simulations that the proposed technique is more robust in the case of 8KH frequency samples.
Index Term-   Analog speech, LPC, PCA, Scramblers, SNR.

 
Introduction:

 
As speech communications become more and more widely used and even more vulnerable, the importance of providing a high level of security is dramatically increasing. As such, a variety of speech encryption techniques have been introduced. The analogue encryption has been one of the most popular encryption techniques widely used in speech communication. In general, there are four main categories: frequency-domain scrambling (e.g., the frequency inverter and the band splitter), time-domain scrambling (e.g., the time element scrambling), amplitude scrambling (also known as the masking technique that covers the speech signal by the linear addition of pseudorandom amplitudes), and two-dimensional scrambling that combines the frequency-domain scrambling with the time-domain scrambling [1, 2]. Besides, there are many other analogue speech encryption methods in the transform domain, e.g., fast Fourier transform, discrete cosine transform and wavelet transform, etc. [3]–[5].