Optimal multiuser spread-spectrum data hiding in digital images

Wei, Lili; Pados, Dimitris A.; Batalama, Stella N.; Hu, Rose Qingyang; Medley, Michael J.

doi:10.1002/sec.1001

Cited by 4 publications

(3 citation statements)

References 34 publications

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“…Furthermore, previous works have shown that feature normalisation and features selection improve performance of classification [19,31]. Equation (29) shows the used feature normalisation…”

Section: Performance Of the Proposed Methodsmentioning

confidence: 99%

“…These methods include Hide4PGP [24], Steghide [21], integer to integer wavelet (i2i) [25]. Also, different spread spectrum methods have been proposed in the literature [5,[26][27][28][29][30]. Among them the DCT-based robust watermarking method (COX) [5], spread spectrum watermarking (SSW) [26], spread spectrum in the frequency domain (SS+DCT) [27], and multi carrier spread spectrum (MCSS) as implemented in [30] were tested in this study.…”

Section: 𝑛[𝑚] = 𝑠[𝑚] − 𝑐[𝑚]mentioning

confidence: 99%

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Universal audio steganalysis based on calibration and reversed frequency resolution of human auditory system

Ghasemzadeh

Arjmandi

2017

IET signal process.

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Calibration and higher order statistics (HOS) are standard components of image steganalysis. However, these techniques have not yet found adequate attention in audio steganalysis. Specifically, most of current studies are either non-calibrated or only based on noise removal. The goal of this paper is to fill these gaps and to show that calibrated features based on re-embedding technique improves performance of audio steganalysis. Furthermore, we show that least significant bit (LSB) is the most sensitive bit-plane to data hiding algorithms and therefore it can be employed as a universal embedding method. The proposed features also benefit from an efficient model which is tailored to the needs for audio steganalysis and represent the maximum deviation from human auditory system (HAS). Performance of the proposed method is evaluated on a wide range of data hiding algorithms in both targeted and universal paradigms. The results show the effectiveness of the proposed method in detecting the finest traces of data hiding algorithms in very low embedding rates. The system detects steghide at capacity of 0.06 bit per symbol (BPS) with sensitivity of 98.6% (music) and 78.5% (speech). These figures are respectively 7.1% and 27.5% higher than the state-of-the-art results based on RMFCC features. 1-the intended message ( ∈ ℳ) inside a host signal, namely called cover ( ∈ ). Steganography methods can be classified into categories of text, audio, image, video, and network traffics, depending on the type of cover signal.Steganalysis is the countermeasure of steganography which aims to detect the presence of hidden messages. Likewise, steganalysis methods may be classified according to the type of cover into categories of text, audio, image, video, and network traffics. Steganalysis in each of these categories can be further divided into targeted and universal methods. In the former, the embedding algorithm is known, whereas there is no prior assumption about the embedding algorithm in the later one [6].One of the first audio steganalysis method was proposed in [7] where cover signal was estimated by de-noising the signal under inspection. Audio quality metrics (AQMs) were used to quantify the discrepancies between the original signal and its estimated cover [7]. Hausdroff distance was proposed as a solution to the inefficiency of AQMs in detecting traces of hidden data [8]. In [9], negative effect of high correlation between the features extracted from these denoising methods and their signals was solved.All of these previous works are similar in that, they have used indirect methods for comparing between stegos and their estimated covers. However, conducting this comparison on the distributions of stegos and covers are more appropriate. This approach was pursued in [10], where it was shown that the degree of histograms flatness derived from wavelet coefficients of stegos and their cover counterparts is a discriminative criterion. Gaussian mixture model (GMM) and generalized Gaussian distribution (GGD) were used to capture this...

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“…Furthermore, previous works have shown that feature normalisation and features selection improve performance of classification [19,31]. Equation (29) shows the used feature normalisation…”

Section: Performance Of the Proposed Methodsmentioning

confidence: 99%

Section: 𝑛[𝑚] = 𝑠[𝑚] − 𝑐[𝑚]mentioning

confidence: 99%

Universal audio steganalysis based on calibration and reversed frequency resolution of human auditory system

Ghasemzadeh

Arjmandi

2017

IET signal process.

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show abstract

“…So it would be very difficult to remove the watermark signal without damaging the host audio integrity. However, traditional SS watermarking methods severely face the host interference problem . As in the case of audio watermarking, the audio signal is very sensitive to additive manipulations.…”

Section: Introductionmentioning

confidence: 99%

Host cancelation‐based spread spectrum watermarking for audio anti‐piracy over Internet

Rong

et al. 2016

Security Comm Networks

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This paper addresses the audio piracy problem over Internet by tweaking data redundancy of host media signal for optimized embedding and extraction of spread spectrum watermarking. In particular, we take into account a special feature that host audio signals have the short‐time stationary property and their major power can be removed using linear prediction filter. By combining the redundancy removing and the improved spread spectrum modulation, host interference is canceled with minimized embedding distortion to the host audio. The data redundancy removing is also applied at the receiver to achieve matched filtering and improved performance. Experiments based on real audio signals show that our proposed scheme performs robustly against various kinds of channel attacks while maintaining high extraction performance. Copyright © 2016 John Wiley & Sons, Ltd.

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A new transform domain steganography based on modified logistic chaotic map for color images

Valandar

Ayubi

Barani

2017

Journal of Information Security and Applications

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Optimal multiuser spread-spectrum data hiding in digital images

Cited by 4 publications

References 34 publications

Universal audio steganalysis based on calibration and reversed frequency resolution of human auditory system

Universal audio steganalysis based on calibration and reversed frequency resolution of human auditory system

Host cancelation‐based spread spectrum watermarking for audio anti‐piracy over Internet

A new transform domain steganography based on modified logistic chaotic map for color images

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