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Different attacks presence considerations: analyzing the simple and efficient self-marked algorithm performance for highly-sensitive audio signals contents verification.

Authors :
El-Bendary, Mohsen A. M.
Nassar, Sabry S.
Source :
International Journal of Speech Technology; Jul2023, Vol. 26 Issue 2, p379-394, 16p
Publication Year :
2023

Abstract

In this research paper, performance of an efficient audio contents integrity verification algorithm using Discrete Cosine Transform (DCT) has been analyzed and studied in presence the different noise and attacks. This approach of audio contents verification is designed based on a self-mark idea, the embedded mark is generated from the same audio file after transforming the sensitive 2-D audio file into two equal size partitions. Integrity and confidentiality verification of classified recorded audio scenario also, has been tested and evaluated in this research paper using the encryption technique to encrypt the marked audio files. Different computer experiments simulation have been executed to evaluate and analysis the performance of the stand-alone self-mark algorithm and with the encryption stage merging. These experiments tested the performance of these two security approaches with presence different attacks. Reverse processes are executed to verify the contents integrity of the audio files. According to the quality of the extracted audio file from the verification process compared to the original audio file, this audio contents integrity algorithm is applicable and robust. Quality of the extracted audio file is evaluated using the different metrics tools. The different attacks are employed to measure the robustness and reliability of this algorithm. The statistical analysis of the results has been presented, it is proved to have high detection sensitivity to observe and discover any audio manipulations even they were inaudible. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13812416
Volume :
26
Issue :
2
Database :
Complementary Index
Journal :
International Journal of Speech Technology
Publication Type :
Academic Journal
Accession number :
169328115
Full Text :
https://doi.org/10.1007/s10772-023-10025-0