An imperceptible, robust, and high payload capacity audio watermarking scheme based on the DCT transformation and Schur decomposition

Karajeh, Huda; Maqableh, Mahmoud

doi:10.1007/s10470-018-1332-0

Cited by 17 publications

(3 citation statements)

References 49 publications

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“…This approach significantly reduces audio degradation and considerably strengthens the robustness of the watermark against attacks such as re-sampling, re-quantization, additive noise, cropping, and MP3 compression. Furthermore, the Schur decomposition can be performed with either DCT or DWT coefficients in audio LSB data hiding as described in [78] and [79], respectively. In these works, the Schur decomposition is used to achieve perceptual transparency of audio watermarking.…”

Section: Transform Domainmentioning

confidence: 99%

“…The two proposed watermarking algorithms follow a similar process: Convert the audio signals into the respective transform domain, apply the Schur decomposition, hide one secret bit into the seventh LSB of selected coefficients, and reconstruct the audio signals in the temporal domain. The algorithm described in [78] utilizes the mid frequency DCT coefficients while the algorithm suggested in [79] selects the second subband (HL2) of 2-level 2D-Haar DWT coefficients. The DCT-Schur decomposition based watermarking algorithm achieves higher capacity than the DWT-Schur decomposition algorithm, but has lower imperceptibility and robustness.…”

Section: Transform Domainmentioning

confidence: 99%

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LSB Data Hiding in Digital Media: A Survey

Tran¹,

Zepernick²,

Chu³

2022

EAI Endorsed Transactions on Industrial Networks and Intelligen

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Data hiding or information hiding is a prominent class of information security that aims at reliably conveying secret data embedded in a cover object over a covert channel. Digital media such as audio, image, video, and three-dimensional (3D) media can act as cover objects to carry such secret data. Digital media security has acquired tremendous significance in recent years and will be even more important with the development and delivery of new digital media over digital communication networks. In particular, least significant bit (LSB) data hiding is easy to implement and to combine with other hiding techniques, offers high embedding capacity for data, can resist steganalysis and several types of attacks, and is well suited for real-time applications. This article provides a comprehensive survey on LSB data hiding in digital media. The fundamental concepts and terminologies used in data hiding are reviewed along with a general data hiding model. The five attributes of data hiding, i.e., capacity, imperceptibility, robustness, detectability, and security, and the related performance metrics used in this survey to compare the characteristics of the different LSB data hiding methods are discussed. Given the classification of data hiding methods with respect to audio, image, video, and 3D media, a comprehensive survey of LSB data hiding for each of these four digital media is provided. In particular, landmark studies, state-of-the-art approaches, and applications of LSB data hiding are described for each of the four digital media. Their performance is compared with respect to the data hiding attributes which illustrates benefits and drawbacks of the reviewed LSB data hiding methods. The article concludes with summarizing main findings and suggesting directions for future research. This survey will be helpful for researchers and practitioners to keep abreast about the potential of LSB data hiding in digital media and to develop novel applications based on suitable performance trade-offs between data hiding attributes.

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Section: Transform Domainmentioning

confidence: 99%

Section: Transform Domainmentioning

confidence: 99%

LSB Data Hiding in Digital Media: A Survey

Tran¹,

Zepernick²,

Chu³

2022

EAI Endorsed Transactions on Industrial Networks and Intelligen

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“…Combination of Schur decomposition and DCT transform was proposed as a new hybrid method in the audio Watermarking area and the desired practical results were obtained [4]. Seyed Mostafa and et al suggest a new watermarking scheme based Lucas regular math sequence and 2-bit embedding procedure.…”

Section: Introductionmentioning

confidence: 99%

High-capacity, transparent and robust blind audio watermarking scheme based DWT and TLBO algorithm

Joudaki

Abdeyazdan

Mosleh

2020

Preprint

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Digital watermarking is one of the best solutions again the copyright infringement, duplicates, verifies data and illegal distribution of digital media. Recently, the protection of digital audio signals is one of the attracting and interesting topics for scientific and researchers. In this paper we propose a blind audio watermarking mechanism in which it has high capacity, transparency and resistance simultaneously based on digital wavelet transform (DWT) algorithm. The key principle of this work is that in the DWT procedure, using two filters; break down the original audio signal into several sub-bands and transform them on a specific frequency range. It should be noted that the 8 bits of watermarked signal is selected and transform to the original signal. In order to increase the watermarking resistance, framing the high frequency coefficients of the third level of the wavelet and calculate the frames average and place them in the frame memory prime. Moreover, TLBO algorithm used to determination of embedding and extraction coefficients in order to increase the SNR ratio in the embedding process and decrease the bit error rate (BER) in the extraction process. This method increases the embedding payload capacity while the audio SNR and extracted image BER have good qualify. Moreover, experimental results shown that this method has 13kbs hiding rate,ascendency imperceptibility, good payload capacity and intense robustness when resisting against various attacks such as MP3 compression, re-quantization, low-pass filtering, amplitude scaling, re-sampling, echo addition and noise corruption.

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