Steganalysis of Quantum Audio Signal using Quantum Support Vector Machine Algorithm

Document Type : Original Article

Authors

1 Department of Computer Engineering, Dezful Branch, Islamic Azad University, Dezful, Iran

2 Islamic Azad University of Dezful

Abstract

With the advent of quantum computing theory and quantum communication networks, establishing confidential and secure communication has become challenging. Quantum audio signal steganalysis is one of the interesting subfields in the field of quantum signal processing and quantum computing, which tries to identify hidden communications in the context of quantum communication networks by using feature extraction techniques and quantum machine learning algorithms. Since steganography causes inevitable changes in the statistical characteristics of the frequency domain of the host signal, it can be used as an efficient and effective tool to build comprehensive and accurate steganalysis. So; At first, the proposed method uses quantum Fourier transform on QRDS audio signal to extract statistical features. For this purpose, the proposed quantum circuit network of these features, quantum spectral center and quantum spectral bandwidth has been designed and implemented. Finally, the Quantum Support Vector Machine (QSVM) algorithm, using the extracted features, separates clean and stego data sets with an accuracy of more than 95%.

Keywords

Smiley face

References

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History

  • Receive Date: 23 January 2023
  • Revise Date: 07 July 2023
  • Accept Date: 26 July 2023
  • Publish Date: 28 September 2023

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