DWT-DCT based blind audio watermarking using Arnold scrambling and Cyclic codes

Subir,; Joshi, Amit M.

doi:10.1109/spin.2016.7566666

Cited by 11 publications

(2 citation statements)

References 9 publications

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“…DCT transformation is used in this work to convert the signal from spatial to frequency domain. DCT [14] transformation decomposes the signal into series of cosine harmonics and it is computationally simple than FFT. One dimensional DCT transformation of signal 𝑓(𝑥) and inverse DCT transformation of 𝐷(𝑛) are shown in Equation (1) and Equation (2).…”

Section: A Discrete Cosine Transform (Dct)mentioning

confidence: 99%

International Journal of Electronics and Telecommunications

Lalitha¹,

Rao

Jayasree³

2019

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Section: A Discrete Cosine Transform (Dct)mentioning

confidence: 99%

International Journal of Electronics and Telecommunications

Lalitha¹,

Rao

Jayasree³

2019

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“…[3] K. Vimal and S. A. kather discussed about extraction of data hidden in the silence region of speech signal by non-voiced detection algorithm. The methodology proposed by Subir and Dr. Amit M. Joshi [3] in their paper uses an innovative approach of Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) for the purpose of watermarking and they incorporated Arnold transformation and error correction technique [4] to increase functioning of the approach. Images are extensively used for process of hiding data in steganography, as audio steganography is perplexing because of higher precision in Human Auditory system (HAS) as compared to Human Visual System(HVS) [5].…”

Section: Introductionmentioning

confidence: 99%

Data Hiding in Speech Signal Using Steganography and Encryption

Karan

Bharath

et al. 2018

2018 3rd IEEE International Conference on Recent Trends in Electronics, Information &Amp; Communication Technology (RTEICT)

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Data privacy and data security are always on highest priority in the world. We need a reliable method to encrypt the data so that it reaches the destination safely. Encryption is a simple yet effective way to protect our data while transmitting it to a destination. The proposed method has state of art technology of steganography and encryption. This paper puts forward a different approach for data hiding in speech signals. A ten-digit number within speech signal using audio steganography and encrypting it with a unique key for better security. At the receiver end the same unique key is used to decrypt the received signal and then hidden numbers are extracted. The proposed approach performance can be evaluated by PSNR, MSE, SSIM and bit-error rate. The simulation results give better performance compared to existing approach.

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