Integration of an RSA-2048-bit public key cryptography solution in the development of secure voice recognition processing applications
Abstract
The authors initially employs the fast Fourier transform (FFT) approach to transforming voice inputs into digital signals before integrating a speech recognition solution (which includes two models: the hidden Markov model (HMM) and the artificial neural network (ANN)). To achieve standard-tone identification of voice signals and digitally store speech, the authors then incorporated a 2048-bit Rivest-Shamir-Adleman (RSA) encryption method to encrypt and decrypt digital speech. The authors’ building team constructed the program using a 256-bit advanced encryption standard - Galois counter mode (AES-GCM) encryption method to assure the application’s effectiveness. The authors successfully created a voice recognition application according to the HMM of ANN. The collected findings suggest that the authors’ secure speech recognition program (named soft voice - RSA) has improved in terms of safety, keeping speech material secret, and speed. It takes roughly 0.2 s to generate a 2048-bit RSA key pair that exceeds the National Institute of Standards and Technology (NIST) standard, 700-1070 ms to process speech, 1-4 ms to encrypt 2048-bit RSA, 6-8 ms to decrypt 2048-bit RSA.
Keywords:
artificial neural network, fast Fourier transform, hidden Markov model, Rivest-Shamir-AdlemanDOI:
https://doi.org/10.31276/VJSTE.65(3).03-07Classification number
1.2
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Published
Received 20 October 2022; revised 20 December 2022; accepted 28 December 2022