An Efficient Hybrid Steganography Method Based on Edge Adaptive and Tree Based Parity Check

Al-Dmour, Hayat; Ali, Noman; Al-Ani, Ahmed

doi:10.1007/978-3-319-14445-0_1

Cited by 4 publications

(5 citation statements)

References 16 publications

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“…An adaptive steganography technique based on Tree-Based Parity Check (TBPC) is proposed in [24]. In a cover image, every two adjacent pixels are paired to form 1x2 sized non-overlapping blocks.…”

Section: Related Workmentioning

confidence: 99%

“…For a comprehensive comparison, Table 6 presents the high visual quality performance of the proposed algorithm with respect to three techniques e.g., PVD (Pixel Value Difference) [31], TBPC (Tree-Based Parity Check) [24] and ATBPC (Adaptive TBPC) [24]. Each given image is evaluated with respect to the PSNR, WPSNRthe and SSIM at the embedding capacity EC of 30% and 50% for 1bpp case.…”

Section: A Embedding Capacity and Image Quality Assessmentmentioning

confidence: 99%

“…On the other hand, the technique of TABLE 6. PSNR, WPSNR and SSIM comparison of proposed method with three techniques [24], [31] and [32]. Edge-XOR embedding calculates pixel difference in limited directions and then uses the average of the differences for the calculation of embedding capacity per pixel.…”

Section: A Embedding Capacity and Image Quality Assessmentmentioning

confidence: 99%

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An Accurate Texture Complexity Estimation for Quality-Enhanced and Secure Image Steganography

et al. 2020

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Content-adaptive steganography intends to hide data in the complex texture content of the image. Recently, some secure steganography methods have been proposed to identify the textural complexity of an image. However, most of the techniques do not take into account the information of pixel variation around the central pixel in all possible directions and therefore they are unable to accurately analyse the texture complexity. This work offers a quality-enhanced and secure method of content-adaptive image steganography. The proposed method is divided into three sequential steps: image segmentation, pixel complexity identification, and data embedding. An input cover image is initially divided into small local regions and the pixel-complexity is identified based on the proposed Complex Block Prior (CBP) criterion. In a local block, a high pass filter (HPF) bank is applied and eight residual responses are obtained. Following the CBP criterion, a complexity level out of nine levels is assigned to an individualized pixel block. The pixels are then arranged in the priority of complexity from highest to lowest. Data embedding for the corresponding complexity level then takes place using the proposed adaptive embedding algorithm. Experimental results verify the preservation of visual quality of stego images produced by the proposed method. Three image datasets: Standard test images, BOWS2 and BOSS-base are used for the experimentation and comparison with prior state-of-art methods. Highest values of the IQ (image quality) parameters e.g., SSIM and WPSNR show the effectiveness of the proposed method.

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Section: Related Workmentioning

confidence: 99%

Section: A Embedding Capacity and Image Quality Assessmentmentioning

confidence: 99%

Section: A Embedding Capacity and Image Quality Assessmentmentioning

confidence: 99%

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An Accurate Texture Complexity Estimation for Quality-Enhanced and Secure Image Steganography

et al. 2020

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“…The said fact is evident from Table V that demonstrates high structural similarity and less interference for our proposed secure bit embedding algorithm. The data for the said table is from the recently published [99], which has referred to the studies of [100][101][102].…”

Section: E Comparative Analysismentioning

confidence: 99%

Prudently Secure Information Theoretic LSB Steganography for Digital Grayscale Images

Rafat¹

2020

IJACSA

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The endangerment of online data breaches calls for exploring new and enhancing existing sneaky ways of clandestine communication to tailor those to match the present and futuristic technological and environmental needs, to which malicious intruders wouldn't have an answer. Cryptography and Steganography are the two distinct techniques that, for long, have remained priority choices for hiding vital information from the unauthorized. But the visibility of the encrypted contents makes these vulnerable to attack. Also, the recent legislative protection agreed to law enforcement authorities in Australia to sneak into pre-shared cryptographic secret keys (PSKs) shall have a devastating impact on the privacy of the people. Hence, the need of the hour is to veil in the encrypted data underneath the cover of Steganography, whose sole intent is to hide the very existence of information. This research endeavor enhances one of the most famous images Steganography technique called the Least Significant Bit (LSB) Steganography, from the security and information-theoretic standpoint by taking a known-cover and known-message attack scenario. The explicit proclamation of this research endeavor is that the security of LSB Steganography lies in inducing uncertainty at the time of bit embedding process. The test results rendered by the proposed methodology confers on the non-detectability and imperceptibility of the confidential information along with its strong resistance against LSB Steganalysis techniques.

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“…Imperceptibility refers to the quality of the stego carrier. The steganography algorithm satisfies the imperceptibility requirement, even though the stego carrier content may differ from the original one if that difference cannot be noticed by the human visual system (HVS) [6]. The imperceptibility is usually computed by the Peak Signal Noise Ratio (PSNR).…”

Section: Introductionmentioning

confidence: 99%

Securing Digital Data: A New Edge Detection and XOR Coding Approach for Imperceptible Image Steganography

Al-Dmour

2023

IJACSA

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The rapid progress of digital devices and technology, coupled with the emergence of the internet has amplified the risks and perils associated with malicious attacks. Consequently, it becomes crucial to protect valuable information transmitted through the internet. Steganography is a tried-and-true technique for hiding information beneath digital content, such as pictures, texts, audio, and video. Various methodologies of image steganography have been developed recently. In image recognition, edge detection secures an image into well-defined areas. This paper introduces a novel image steganography algorithm with edge detection and XOR coding techniques. The proposed approach aims to conceal a confidential message within the spatial domain of the original image. In contrast to uniform regions, the Human Visual System (HVS) is less responsive to variations in the sharp areas; an edge detection algorithm is applied to identify edge pixels. Furthermore, to enhance the efficiency and reduce the embedding impact, XOR operation has been utilized to embed the secret message in the Least Significant Bit (LSB). According to the results of the experiments, the proposed method embeds confidential data without causing noticeable modifications to the stego image. The proposed method system produced imperceptible stego images with minimal embedding distortions compared to existing methods. Based on the results, the proposed approach outperforms the conventional methods regarding image distortion techniques. The PSNR values achieved by the proposed method are higher than the acceptable level.

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An Efficient Hybrid Steganography Method Based on Edge Adaptive and Tree Based Parity Check

Cited by 4 publications

References 16 publications

An Accurate Texture Complexity Estimation for Quality-Enhanced and Secure Image Steganography

An Accurate Texture Complexity Estimation for Quality-Enhanced and Secure Image Steganography

Prudently Secure Information Theoretic LSB Steganography for Digital Grayscale Images

Securing Digital Data: A New Edge Detection and XOR Coding Approach for Imperceptible Image Steganography

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