Histogram estimation-scheme-based steganalysis defeating the steganography using pixel-value differencing and modulus function

Joo, Jeong-Chun; Kim, Kyung Soo; Lee, Heung-Kyu; Lee, Hae-Yeoun

doi:10.1117/1.3463021

Cited by 4 publications

(3 citation statements)

References 16 publications

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“…In this paper Jeong-Chun Joo Kyung-Su Kim and Heung-Kyu Lee presented a specific steganalysis method to defeat the modulus Pixel Value Differencing (PVD) steganography [7]. By analyzing the embedding process they provided three blind Support Machines (SMs) for the steganalysis and each are used for checking three different features.…”

Section: Histogram Estimation Scheme For Defeating Pixel Value Differmentioning

confidence: 98%

A Novel Steganalysis Method Based on Histogram Analysis

Choudhury

Das

Baruah

2014

Lecture Notes in Electrical Engineering

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Steganalysis is the art of detecting hidden messages embedded inside Steganographic Images. Steganalysis involves detection of steganography, estimation of message length and its extraction. Recently Steganalysis receives great deal of attention from the researchers due to the evolution of new, advanced and much secured steganographic methods for communicating secret information. This paper presents a universal steganalysis method for blocking recent steganographic techniques in spatial domain. The novel method analyses histograms of both the cover and suspicious image and based on the histogram difference it gives decision on the suspicious image of being stego or normal image. This method for steganalysis extracts a special pattern from the histogram difference of the cover and . By finding that specific pattern from the histogram difference of the suspicious and cover image it detects the presence of hidden message. The proposed steganalysis method has been experimented on a set of stego images where different steganographic techniques are used and it successfully detects all those stego images.

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Section: Histogram Estimation Scheme For Defeating Pixel Value Differmentioning

confidence: 98%

A Novel Steganalysis Method Based on Histogram Analysis

Choudhury

Das

Baruah

2014

Lecture Notes in Electrical Engineering

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“…Studies have proposed steganalysis methods based on machine learning and deep learning methods [32,33], but these techniques require considerable computing resources. In a statistical characteristic-based steganalysis, Joo et al [34] used the changes in a pixel difference histogram (PDH) to detect modulus PVD steganography. Zaker et al [35] also used PDH to detect tri-way PVD, and Zhang et al [36] proposed PVD noise steganalysis with weighted stego image (WS) estimators.…”

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confidence: 99%

Statistical Feature–Based Steganalysis for Pixel-Value Differencing Steganography

Lin¹,

Lai

Chang³

2021

Preprint

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The security and embedding capacity of pixel-value differencing (PVD) steganography is superior to that of least significant bit replacement steganography. Several studies have proposed extended PVD steganography methods that use the original concept of PVD steganography. The majority of the studies have verified their security against regular-singular detection analysis or pixel difference histogram attacks. Weighted stego image steganalysis is the state-of-the-art technology for PVD steganography. This study proposed a suitable parameter for the estimator based on different relative embedding ratios and the size of normal embedding blocks. The experimental results revealed that the proposed technology does not require advance knowledge of the original image. In addition, the proposed method is accurate and precise at any embedding ratio. In the future, this method may be utilized to analyze the security of extended PVD steganography.

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“…Subsequently, because the embedding process of MFPVD steganography [26] generates fluctuations and growing abnormalities, the asymmetry on the PDH is created. The steganalysis of MFPVD [26] was proposed by Joo et al [45], which utilizes these features to detect the embedding messages.…”

mentioning

confidence: 99%

Statistical feature-based steganalysis for pixel-value differencing steganography

Lin

Lai

Chang

2021

EURASIP J. Adv. Signal Process.

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Pixel-value differencing (PVD) steganography is a popular spatial domain technology. Several PVD-based studies have proposed extended PVD steganography methods. The majority of these studies have verified their security against the regular-singular (RS) analysis. However, RS analysis is aimed at the feature of the least significant bit substitution method, which is relatively less significant for PVD steganography. The pixel difference histogram (PDH) is generally utilized to attack PVD steganography. If the embedding capacity is high, then the features on the PDH are evident; otherwise, the features are less obvious. In this paper, we propose a statistical feature-based steganalysis technique for the original PVD steganography. Experimental results demonstrate that, compared with existing steganalysis technique with weighted stego-image (WS) method, the proposed method effectively detects PVD steganography at low embedding ratios, such that there is no need of using the original embedding parameters. Furthermore, the accuracy and precision of the method are better than those of existing PVD steganalysis techniques. Therefore, the proposed method contributes to the security analysis of the original PVD steganography as an alternative to the commonly used RS, PDH and WS attack techniques.

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Histogram estimation-scheme-based steganalysis defeating the steganography using pixel-value differencing and modulus function

Cited by 4 publications

References 16 publications

A Novel Steganalysis Method Based on Histogram Analysis

A Novel Steganalysis Method Based on Histogram Analysis

Statistical Feature–Based Steganalysis for Pixel-Value Differencing Steganography

Statistical feature-based steganalysis for pixel-value differencing steganography

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