Application of Walsh Transformations for Encryption and Decryption of Audio Signals

<p><strong><span>This paper explores using the Walsh-Hadamard Transform (WHT) to encrypt and decrypt audio signals. WHT, known for its computational efficiency and orthogonality properties, enables the decomposition of a signal into spectral coefficients, which can then be securely masked using a random key. Additionally, the article investigates the application of the Discrete Cosine Transform (DCT) alongside WHT and their combined variant (DCT-WHT) for encrypting and decrypting audio signals. WHT, characterized by its high computational speed, and DCT, known for its high accuracy, demonstrate significant efficiency in the encryption and decryption process [1], [2]. The study provides a detailed algorithm for preprocessing signals, including normalization, padding signal lengths to the nearest power of two, and applying forward and inverse WHT transformations. A novel masking technique is introduced, leveraging the properties of Walsh basis functions to enhance data security. Practical implementation involves converting input audio signals into WAV format, applying the WHT or the combined DCT-WHT approach, encrypting the coefficients with a random key, and reconstructing the original signal using inverse transformations. The proposed methods ensure reconstruction accuracy exceeding 99.9%, maintaining high fidelity while providing robust attack resistance. This approach efficiently transmits audio data securely in communication systems, multimedia applications, and other areas requiring robust encryption mechanisms. Additionally, the study explores the possibility of combining WHT with other signal processing algorithms, such as DCT or the Fourier Transform, to further enhance security features. The combined use of these methods improves resistance to attacks through multi-layer spectral transformation of the signal while retaining computational efficiency and noise resilience [1], [2]. The study highlights the promise of the DCT-WHT approach as a versatile and adaptable tool within modern cryptographic frameworks, offering a simple yet effective solution for the secure transmission and processing of audio data<span>  </span>[2].</span></strong></p>

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-06
DOI
https://doi.org/10.5281/zenodo.14977970
Primary Topic
Medical Malpractice and Liability Issues
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Application of Walsh Transformations for Encryption and Decryption of Audio Signals

Zenodo (CERN European Organization for Nuclear Research)
Medical Malpractice and Liability Issues
article

Application of Walsh Transformations for Encryption and Decryption of Audio Signals

article en

Abstract

<p><strong><span>This paper explores using the Walsh-Hadamard Transform (WHT) to encrypt and decrypt audio signals. WHT, known for its computational efficiency and orthogonality properties, enables the decomposition of a signal into spectral coefficients, which can then be securely masked using a random key. Additionally, the article investigates the application of the Discrete Cosine Transform (DCT) alongside WHT and their combined variant (DCT-WHT) for encrypting and decrypting audio signals. WHT, characterized by its high computational speed, and DCT, known for its high accuracy, demonstrate significant efficiency in the encryption and decryption process [1], [2]. The study provides a detailed algorithm for preprocessing signals, including normalization, padding signal lengths to the nearest power of two, and applying forward and inverse WHT transformations. A novel masking technique is introduced, leveraging the properties of Walsh basis functions to enhance data security. Practical implementation involves converting input audio signals into WAV format, applying the WHT or the combined DCT-WHT approach, encrypting the coefficients with a random key, and reconstructing the original signal using inverse transformations. The proposed methods ensure reconstruction accuracy exceeding 99.9%, maintaining high fidelity while providing robust attack resistance. This approach efficiently transmits audio data securely in communication systems, multimedia applications, and other areas requiring robust encryption mechanisms. Additionally, the study explores the possibility of combining WHT with other signal processing algorithms, such as DCT or the Fourier Transform, to further enhance security features. The combined use of these methods improves resistance to attacks through multi-layer spectral transformation of the signal while retaining computational efficiency and noise resilience [1], [2]. The study highlights the promise of the DCT-WHT approach as a versatile and adaptable tool within modern cryptographic frameworks, offering a simple yet effective solution for the secure transmission and processing of audio data<span>  </span>[2].</span></strong></p>

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 39%
Medical Malpractice and Liability Issues
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.