Information Hiding in RGB Images Using an Improved Matrix Pattern Approach

Nilizadeh, Amirfarhad; Mazurczyk, Wojciech; Zou, Cliff C.; Leavens, Gary T.

doi:10.1109/cvprw.2017.183

Cited by 17 publications

(19 citation statements)

References 29 publications

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“…1. This work supports all 256 ASCII characters, while the earlier MP works [49,51,54,83] supported only 49 and 95 English keyboard characters. Thus, any digital media can be hidden as a message like a cryptographically encoded message.…”

Section: Introductionmentioning

confidence: 94%

Adaptive Matrix Pattern Steganography on RGB Images

Nilizadeh

Mazurczyk

et al. 2021

JCSANDM

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Almost all spatial domain image steganography methods rely on modifying the Least Significant Bits (LSB) of each pixel to minimize the visual distortions. However, these methods are susceptible to LSB blind attacks and quantitative steganalyses. This paper presents an adaptive spatial domain image steganography algorithm for hiding digital media based on matrix patterns, named “Adaptive Matrix Pattern” (AMP). The AMP method increases the security of the steganography scheme of largely hidden messages since it adaptively generates a unique codebook matrix pattern for each ASCII character in each image block. Therefore, each ASCII character gets a different codebook matrix pattern even in different regions of the same image. Moreover, it uses a preprocessing algorithm to identify the most suitable image blocks for hiding purposes. The resulting stego-images are robust against LSB blind attacks since the middle bits of green and blue channels generate matrix patterns and hiding secrets, respectively. Experimental results show that AMP is robust against quantitative steganalyses. Additionally, the quality of stego-images, based on the peak signal-to-noise ratio metric, remains high in both stego-RGB-image and in the stego-blue-channel. Finally, the AMP method provides a high hiding capacity, up to 1.33 bits per pixel.

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Section: Introductionmentioning

confidence: 94%

Adaptive Matrix Pattern Steganography on RGB Images

Nilizadeh

Mazurczyk

et al. 2021

JCSANDM

Self Cite

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“…The authors also tested their scheme against many frequency and spatial domain attacks such as: RS, Sample pair, X2 and DCT based attacks, and were able to prove its resiliency against malicious efforts. The authors of [18] also propose a steganography technique based on matrix patterns. The RGB image is first divided into square sized blocks then 95 matrix patterns are automatically formed using the 4th and 5th bit layers of the green layer of each block.…”

Section: Introductionmentioning

confidence: 99%

“…The scheme was shown to have high resistance against steganalysis attacks including Regular Singular, Sample Pair, and PVD based attacks and has higher capacity than [17]. In [19], a combination of two steganography techniques is proposed, matrix pattern steganography such as in [17] and [18], and standard LSB substitution. The matrix pattern technique first divides the RGB coverimage into a number of non-overlapping blocks.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study Among Different Mathematical Sequences in 3D Image Steganography

Alexan¹,

Beheiry²,

Gamal–Eldin³

2020

IJCDS

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This paper proposes a double-layer message security scheme. The message is first encrypted using AES-128 and is then embedded within a 3D image using least significant bit (LSB) substitution. The LSB substitution is carried out using multiple mathematical sequences and a comparison between the performance of each sequence is investigated. The proposed system is evaluated using a number of performance metrics including the mean square error (MSE), the peak signal to noise ratio (PSNR), the entropy, the mean structural similarity index measurement (MSSIM), the R measurement, the normalized cross correlation (NCC), the image fidelity (IF) and the image distance (ID). Furthermore, a comparison between the proposed schemes and other proposed works from the literature is performed to demonstrate its superiority.

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“…Biometric technology, which is widely spread due to its high accuracy and user friendliness, is currently employed for recognizing individuals via measurable physiological or behavioural properties [8]. To the best of our knowledge, the physiological properties include fingerprint [9], iris [10], and face [11], while the behavioural properties include tread [12], signature [13], and voice [14]. To this end, by transferring the biometric properties into electric signals, we are thus able to get insight into the system of using biometrics to describe individuals [15].…”

Section: Introductionmentioning

confidence: 99%

Remote Identity Verification Using Gait Analysis and Face Recognition

Zhang

et al. 2020

Wireless Communications and Mobile Computing

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Biometric identification has verified its effectiveness in personal identity verification because of the uniqueness and noninvasion. In this research, we tend to apply the detection of biometric information to a remote sensing system for the purpose of security area monitoring. Our system is established by collecting signals from the coming individuals via the remote measurement in the specific condition where both kinds of data are detected to determine the identity. Specifically, the measuring of gait signals and facial images is integrated to provide a way of improving the detection accuracy and the robustness. In addition, the fuzzy association rule (FAR) is employed for data analysis in line with the outcomes of different methods. As such, the signals are integrated and transmitted for further processing and remote identification. Experiments are conducted to demonstrate the capability of the proposed system. With the training data increases, a high detection accuracy of 95.2% is obtained, which makes it a promising basis for the realization of remote identity verification.

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Information Hiding in RGB Images Using an Improved Matrix Pattern Approach

Cited by 17 publications

References 29 publications

Adaptive Matrix Pattern Steganography on RGB Images

Adaptive Matrix Pattern Steganography on RGB Images

A Comparative Study Among Different Mathematical Sequences in 3D Image Steganography

Remote Identity Verification Using Gait Analysis and Face Recognition

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