High capacity, transparent and secure audio steganography model based on fractal coding and chaotic map in temporal domain

Ali, Ahmed Hussain; George, Loay E.; Zaidan, A. A.; Mokhtar, Mohd Rosmadi

doi:10.1007/s11042-018-6213-0

Cited by 60 publications

(37 citation statements)

References 42 publications

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“…A digital watermark is called imperceptible if the original and watermarked images are perceptually indistinguishable. It might be fulfilled by sacrificing either robustness, capacity or both [7]. Robustness indicates the ability of the watermarking scheme to resist to different image processing operations.…”

Section: Imperceptibilitymentioning

confidence: 99%

Assessment of perceptual distortion boundary through applying reversible watermarking to brain MR images

Qasim

Aspin

Meziane

et al. 2019

Signal Processing: Image Communication

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The digital medical workflow faces many circumstances in which the images can be manipulated during viewing, extracting and exchanging. Reversible and imperceptible watermarking approaches have the potential to enhance trust within the medical imaging pipeline through ensuring the authenticity and integrity of the images to confirm that the changes can be detected and tracked. This study concentrates on the imperceptibility issue. Unlike reversibility, for which an objective assessment can be easily made, imperceptibility is a factor of human cognition that needs to be evaluated within the human context. By defining a perceptual boundary of detecting the modification, this study enables the formation of objective guidelines for the method of data encoding and level of image/pixel modification that translates to a specific watermark magnitude. This study implements a relative Visual Grading Analysis (VGA) evaluation of 117 brain MR images (8 original and 109 watermarked), modified by varying techniques and magnitude of image/pixel modification to determine where this perceptual boundary exists and relate the point at which change becomes noticeable to the objective measures of the image fidelity evaluation. The outcomes of the visual assessment were linked to the images Peak Signal to Noise Ratio (PSNR) values, thereby identifying the visual degradation threshold. The results suggest that, for watermarking applications, if a watermark is applied to the 512x512 pixel (16 bpp grayscale) images used in the study, a subsequent assessment of PSNR=82dB or greater would mean that there would be no reason to suspect that the watermark would be visually detectable.

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Section: Imperceptibilitymentioning

confidence: 99%

Assessment of perceptual distortion boundary through applying reversible watermarking to brain MR images

Qasim

Aspin

Meziane

et al. 2019

Signal Processing: Image Communication

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“…In the other side, there is a huge amount of information in social networks now and it's not difficult to hide a message in one way or another [5], [7]. In this case, if the disguised message under the typical content of a social network, then will be quite problematic to detect the fact of hiding information [1], [8], [9]. This information may be, for example, images or audio and hiding one at the other is a required task.…”

Section: Introductionmentioning

confidence: 99%

Audio steganography based on least significant bits algorithm with 4D grid multi-wing hyper-chaotic system

Abdulkadhim

Shehab

2022

IJECE

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Although variety in hiding methods used to protect data and information transmitted via channels but still need more robustness and difficulty to improve protection level of the secret messages from hacking or attacking. Moreover, hiding several medias in one media to reduce the transmission time and band of channel is the important task and define as a gain channel. This calls to find other ways to be more complexity in detecting the secret message. Therefore, this paper proposes cryptography/steganography method to hide an audio/voice message (secret message) in two different cover medias: audio and video. This method is use least significant bits (LSB) algorithm combined with 4D grid multi-wing hyper-chaotic (GMWH) system. Shuffling of an audio using key generated by GMWH system and then hiding message using LSB algorithm will provide more difficulty of extracting the original audio by hackers or attackers. According to analyses of obtained results in the receiver using peak signal-to-noise ratio (PSNR)/mean square error (MSE) and sensitivity of encryption key, the proposed method has more security level and robustness. Finally, this work will provide extra security to the mixture base of crypto-steganographic methods.

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“…The essential requirements for audio steganography are: (1) the secret data should not be perceptible to humans [6,7]; (2) it should maximize the hiding capacity; and (3) preferably, the hidden data should be encrypted. In the digital world, two types of objects are used: either audio or image files as stego-objects for masking the furtive message [9]. By performing a bit change in the binary sequence of a sound file, the secret data are embedded into the original file.…”

Section: Introductionmentioning

confidence: 99%

A Novel Steganography Approach for Audio Files

2020

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We present a novel robust and secure steganography technique to hide images into audio files aiming at increasing the carrier medium capacity. The audio files are in the standard WAV format, which is based on the LSB algorithm, while images are compressed by the GMPR technique which is based on the Discrete Cosine Transform and high-frequency minimization encoding algorithm. The method involves compression-encryption of an image file by the GMPR technique followed by hiding it into audio data by appropriate bit substitution. The maximum number of bits without significant effect on audio signal for LSB audio steganography is 6 LSBs. The encrypted image bits are hidden into variable and multiple LSB layers in the proposed method. Experimental results from observed listening tests show that there is no significant difference between the stego-audio reconstructed from the novel technique and the original signal. A performance evaluation has been carried out according to quality measurement criteria of signal-to-noise ratio and peak signal-to-noise ratio.

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High capacity, transparent and secure audio steganography model based on fractal coding and chaotic map in temporal domain

Cited by 60 publications

References 42 publications

Assessment of perceptual distortion boundary through applying reversible watermarking to brain MR images

Assessment of perceptual distortion boundary through applying reversible watermarking to brain MR images

Audio steganography based on least significant bits algorithm with 4D grid multi-wing hyper-chaotic system

A Novel Steganography Approach for Audio Files

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