Self-generated model of acoustics encryption by means of true random number generator

O. Safaryan; L. Cherckesova; N. Gapon; I. Alferova; B. Akishin; E. Semenishchev

doi:10.1117/12.3017674

7 June 2024 Self-generated model of acoustics encryption by means of true random number generator

O. Safaryan, L. Cherckesova, N. Gapon, I. Alferova, B. Akishin, E. Semenishchev

Proceedings Volume 13057, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXIII; 1305713 (2024) https://doi.org/10.1117/12.3017674
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Conference Poster

Abstract

In recent years, the random number generators in engineering applications have attracted the attention of many researchers. One of the most important aspects is to obtain some sequences of both truly random and pseudorandom numbers that can be applicated in the various fields of cryptography, signal processing, and in many other fields of engineering. At the production of pseudorandom number generators, chaotic maps are the source of entropy to create some randomness. Most of the methods based on chaotic maps have been attacked easily in recent years with the help of nonlinear prediction (forecasting), as well as analysis of the phase space on the map. A true random number generator is actual area of research when using in it the encryption. Encryption of any data with random source ensures the security of information. The purpose of this article is to develop the self-generated truly random numbers for audio encryption. For this aim, a sound encryption system was created. Digital audio data is converted to binary form. The XOR operation is performed to develop for truly random number generator. The testing systems NIST 800–22 Test Suite and TestU01 are ap-plied to the bit stream. The source data and the encryption key are evaluated for randomness. Audio encryption is performed with the generated bits. This article proves that the self–generated audio encryption system can be implemented. Statistical analysis and data distribution show that the encryption process with self–generation is successful. In this paper, the authors propose the model of sound encryption of self-generated true random number.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

O. Safaryan, L. Cherckesova, N. Gapon, I. Alferova, B. Akishin, and E. Semenishchev "Self-generated model of acoustics encryption by means of true random number generator", Proc. SPIE 13057, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXIII, 1305713 (7 June 2024); https://doi.org/10.1117/12.3017674

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available