Steganography with pixel-value differencing and modulus function based on PSO

Li, Zhaotong; He, Ying

doi:10.1016/j.jisa.2018.10.006

Cited by 36 publications

(30 citation statements)

References 11 publications

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“…The proposed method is compared with popular counterparts spatial PVD-based steganography methods, including Wu and Tsai [11], Wu et al [54], Wang et al [18], Yang et al [19], Liao et al [20], Hussain et al [14], and Li and He [25]. These methods are all spatial domains based on the PVD technique similar to the proposed method.…”

Section: E Comparison With the State-of-the-art 1) Comparison With Pvd-based Steganography Methodsmentioning

confidence: 99%

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An Adaptive Image Steganography Method Based on Histogram of Oriented Gradient and PVD-LSB Techniques

Hameed¹,

Hassaballah

Aly

et al. 2019

IEEE Access

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Pixel value differencing (PVD) and least significant bit substitution (LSB) are two widely used schemes in image steganography. These two methods do not consider different content in a cover image for hiding the secret data. The content of most digital images has different edge directions in each pixel, and the local object shape or appearance is mostly characterized by the distribution of its intensity gradients or edge directions. Exploiting these characteristics for embedding various secret information in different edge directions will eliminate sequential embedding and improve robustness. Thus, a histogram of oriented gradient (HOG) algorithm is proposed to find the dominant edge direction for each 2 × 2 block of cover images. Blocks of interest (BOIs) are determined adaptively based on the gradient magnitude and angle of the cover image. Then, the PVD algorithm is used to hide secret data in the dominant edge direction, while the LSB substitution is utilized in the other two remaining pixels. Extensive experiments using various standard images reveal that the proposed scheme provides high embedding capacity and better visual quality compared with several other PVD-and LSB-based methods. Moreover, it resists various steganalysis techniques, such as pixel difference histogram and RS analysis.INDEX TERMS Data hiding, steganography, pixel value differencing, least significant bit, histogram of oriented gradient, HOG.

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Section: E Comparison With the State-of-the-art 1) Comparison With Pvd-based Steganography Methodsmentioning

confidence: 99%

“…The selective property of the proposed method not only improves the visual quality of the stego image but also increases the embedding capacity. Additionally, Li and He [25] proposed a data hiding algorithm using PVD, modulus function and particle swarm optimization to improve embedding capacity and visual quality.…”

Section: Related Workmentioning

confidence: 99%

An Adaptive Image Steganography Method Based on Histogram of Oriented Gradient and PVD-LSB Techniques

Hameed¹,

Hassaballah

Aly

et al. 2019

IEEE Access

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“…For example, capacity improvement generally has a negative influence on invisibility Public key steganography: like in cryptography, A uses the public key of B when it wants to send a message to it. B extract with its private key [8] (Figure 4).…”

Section: Steganography Characteristicsmentioning

confidence: 99%

Steganographic Techniques Classification According to Image Format

Khaldi

2019

Int. Ann. Sci.

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In this work, we present a classification of steganographic methods applicable to digital images. We also propose a classification of steganographic methods according to the type of image used. We noticed there are no methods that can be applied to all image formats. Each type of image has its characteristics and each steganographic method operates on a precise colorimetric representation. This classification provides an overview of the techniques used for the steganography of digital images

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“…In recent years, many studies have been conducted to improve the capacity, safety and stego image quality using PVD-based methods [31][32][33][34][35][36]. In the article, GUI which makes it easy to hide the data in the agricultural databases to cover images and extract the hidden data from the stego image was designed to effectively use image steganography in the field of agriculture.…”

Section: Introductionmentioning

confidence: 99%