Mazdak Technique for PSNR Estimation in Audio Steganography

Zamani, Mazdak; Azizah, Bt Abdul Manaf; Shahidan, M.A; Saman, Shojae Chaeikar

doi:10.4028/www.scientific.net/amm.229-231.2798

Cited by 9 publications

(6 citation statements)

References 9 publications

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“…Furthermore, the result shows that the difference between estimation and the actual value is less than 0.1 at different levels. A comparison was made between the proposed method and Mazdak Method (Mazdak et al, 2012). Mazdak Method focuses on estimating PSNR at different bps rates to cater for the trade-off between capacity and imperceptibility.…”

Section: Evaluation and Discussionmentioning

confidence: 99%

“…Therefore, although several advantages can be achieved by estimating the PSNR, only one research has proposed on PSNR estimation in audio steganography. Mazdak et al (2012) proposed a PSNR estimation method based on linear interpolation formula. The method uses PSNR value and bit per sample (BPS) rate on existing stego-file to estimate PSNR value of new stego-file that embed different bps rate.…”

Section: Related Workmentioning

confidence: 99%

“…The most common existing audio steganography methods are phase coding, Least Significant Bit (LSB) modification, echo hiding, parity coding, wavelet domain and spread spectrum (Mazdak et al, 2012). This research focuses on the LSB modification because of its simplicity, flexibility to modification, efficiency, high imperceptibility and capacity (Asad et al, 2011;Djebbar et al, 2011;Tayel et al, 2016;Mazdak et al, 2012). However, although it has numerous advantages, it has low robustness features and is easy to extract (Cvejic & Seppänen, 2005;Kanhe et al, 2015;Meligy et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…The method to estimate the PSNR, also known as PE, will enable early evaluation on imperceptibility feature for each stego-file produced by the audio steganography that can be used as a reference for utilisation of embedding. Additionally, in a real-time application, computational complexity is crucial to ensure an audio steganography implementation (Mazdak et al, 2012). Therefore, PE can avoid repetitive embedding processes in finding the feasible solution for the trade-off, further reducing the computational complexity.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A New Method to Estimate Peak Signal to Noise Ratio for Least Significant Bit Modification Audio Steganography

Azam¹,

Ridzuan²,

Sayuti³

2022

JST

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Audio steganography is implemented based on three main features: capacity, robustness, and imperceptibility, but simultaneously implementing them is still a challenge. Embedding data at the Least Significant Bit (LSB) of the audio sample is one of the most implemented audio steganography methods because the method will give high capacity and imperceptibility. However, LSB has the lowest robustness among all common methods in audio steganography. To cater to this problem, researchers increased the depth of the embedding level from fourth to sixth and eighth LSB level to improve its robustness feature. However, consequently, the imperceptibility feature, which is commonly measured by Peak Signal to Noise Ratio (PSNR), is reduced due to the trade-off between imperceptibility and robustness. Currently, the lack of study on the estimation of the PSNR for audio steganography has caused the early assessment of the imperceptibility-robustness trade-off difficult. Therefore, a method to estimate PSNR, known as PSNR Estimator (PE), is introduced to enable early evaluation of imperceptibility feature for each stego-file produced by the audio steganography, which is important for the utilisation of embedding. The proposed PE estimates the PSNR based on the pattern collected from the embedment at different levels. From the evaluation, the proposed method has 99.9% of accuracy in estimating PSNR values at different levels. In comparison with the Mazdak Method, the proposed method performs better in all situations. In conclusion, the proposed PE can be used as a reference for embedding and further reducing the calculation complexity in finding the feasible value to minimise the trade-off between robustness and imperceptibility.

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Section: Evaluation and Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A New Method to Estimate Peak Signal to Noise Ratio for Least Significant Bit Modification Audio Steganography

Azam¹,

Ridzuan²,

Sayuti³

2022

JST

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show abstract

“…This is a metric for evaluating the recovery ability and the extent of image noise after recovery, based on a calculation of peak signal-to-noise ratio (PSNR) and the normalized mean square error (MSE) [39]. It is calculated by:…”

Section: Psnr and Mse Analysismentioning

confidence: 99%

Secure and Low-Complexity Medical Image Exchange Based on Compressive Sensing and LSB Audio Steganography

Al-Chaab,

Abduljabbar,

Abood

et al. 2023

IJCAI

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Patients' data constitutes the vast majority of information exchanged over the Internet. The magnitude of maintaining its security and privacy directly correlates to the importance and privacy of the patients themselves. The manipulation of this data negatively impacts the patient's life and treatment, thus the researchers were inclined to find solutions for this confidentiality challenge by concealing the data to prevent unauthorized access. The process of data concealment is more complex when dealing with large amounts of data. Often, the proportions of the medical image are sizable, which creates challenges when compressing data while maintaining high accuracy. In this paper, a system for securing and compressing medical images based on the Compressive Sensing (CS) principle is presented. The medical image is divided into 8×4 sub-matrices that are multiplied by a 3×8 sensor matrix consisting of Gaussian random numbers. The proposed solution reduces the image's original size by about 30% and conceals it as a random distribution inside an audio (wav) file for more security, using the LSB technique for low complexity. For reconstruction, the sensed image is multiplied by the pseudo-inverse of Moore-Penrose. The statistical analysis proved the efficacy of the system in compression and recovery with reduced cost and time consumption, combined with reduced distortion of the cover file; it was also judged to be increasingly efficient compared to previous research.Povzetek: V tem članku je predstavljen sistem za varovanje in stiskanje medicinskih slik na principu kompresijskega zaznavanja (CS).

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VW16E: A Robust Video Watermarking Technique Using Simulated Blocks

Arab

Zamani

2016

Intelligent Systems Reference Library

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Mazdak Technique for PSNR Estimation in Audio Steganography

Abstract: A novel method to estimate PSNR of the result of audio steganography before embedding is presented. Estimated PSNR by proposed linear interpolation formula was tested and the result was almost the same with the obtained PSNR in practical way.

Cited by 9 publications

References 9 publications

A New Method to Estimate Peak Signal to Noise Ratio for Least Significant Bit Modification Audio Steganography

A New Method to Estimate Peak Signal to Noise Ratio for Least Significant Bit Modification Audio Steganography

Secure and Low-Complexity Medical Image Exchange Based on Compressive Sensing and LSB Audio Steganography

VW16E: A Robust Video Watermarking Technique Using Simulated Blocks

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