Steganographic on Pixel Value Differencing in Iris Biometric

Mansor, Nur Khaleeeda; Asraf, Syed Muhammad Hazry; Idrus, Syed Zulkarnain Syed

doi:10.1088/1742-6596/1529/3/032078

Cited by 5 publications

(5 citation statements)

References 5 publications

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“…Text data is encrypted before being embedded, and various statistical measures are applied to ensure the imperceptibility of the cover medium. The statistical scoring method is found to be effective in concealing secret textual information, which outperforms other existing techniques [29]. Biometric systems face numerous challenges related to security and data integrity.…”

Section: Literature Reviewmentioning

confidence: 95%

Dynamic 8-bit XOR algorithm with AES crypto algorithm for image steganography

Madhu,

Vasuhi,

Samydurai

2024

SIViP

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The expansion of the Internet's infrastructure has brought images to the forefront of multimedia content, leading to the use of image steganography as a means of hiding confidential data. This research proposes a novel method that combines the dynamic 8-bit XOR algorithm and the Advanced Encryption Standard (AES) crypto algorithm to enhance the security and robustness of image steganography. The proposed algorithm encrypts the message using AES and conceals it within the image using the dynamic XOR algorithm. The performance of the method is evaluated based on various objectives, including the impact of secret message size and stego image saving size. Histogram analysis is conducted to assess the pixel value distribution and frequency in the original and stego images. The results demonstrate minimal differences between the histograms, indicating the difficulty in detecting hidden information. Performance evaluation metrics such as Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), Normalized Pixel Change Rate (NPCR), and entropy are utilized to quantify the algorithm's performance. The impact of the secret message size is investigated, showing a trade-off between text size and PSNR performance.Increasing the secret message size leads to a decrease in PSNR and an increase in MSE.NPCR analysis reveals that a smaller secret message size results in a higher NPCR value, indicating stronger concealment capabilities. Entropy analysis demonstrates a remarkable proximity to the ideal entropy value. Furthermore, the impact of stego image saving size is evaluated. Results show that higher stego image dimensions result in higher PSNR values, indicating better image quality. Entropy values remain close to the ideal level for different stego image sizes. NPCR values decrease with larger stego image dimensions, indicating reduced concealment capabilities. Overall, the proposed method offers a comprehensive assessment of its capabilities as a reliable image steganography technique. The combination of encryption and dynamic XOR algorithm enhances security and robustness. The evaluation metrics provide objective measures to assess the quality, security, and efficiency of the algorithm. The research contributes to the field of image steganography and highlights the potential for real-world applications.

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Section: Literature Reviewmentioning

confidence: 95%

Dynamic 8-bit XOR algorithm with AES crypto algorithm for image steganography

Madhu,

Vasuhi,

Samydurai

2024

SIViP

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“…However, the PVD method can store a larger number of data bits without losing the image quality, while an LSB can store a large number of data bits but degrades the image quality. Mansor et al [6] proposed the technique of 2D discrete wavelet transforms in two levels for embedding patients' data in a cover medium. For cover images, they used colour images and grayscale images.…”

Section: Preliminariesmentioning

confidence: 99%

“…Greyscales images only contain the intensity data using a single sample value for each pixel. It is usually called black and white, and these images contain the different shades of grey (0 to 255), in which the black color is at 0, and it represents the weak intensity, while the white color is at 255, and it represents the vigorous-intensity whereas color images consist of three primary sets of colors red, green and blue ranging color from 0-255 [6]. However, in the spatial domain watermarking, the modification of cover image pixel with watermark image is applied.…”

Section: Introductionmentioning

confidence: 99%

A Robust Data Hiding Reversible Technique for Improving the Security in e-Health Care System

Kanwal¹,

Feng²,

Almogren³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

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The authenticity and integrity of healthcare is the primary objective. Numerous reversible watermarking schemes have been developed to improve the primary objective but increasing the quantity of embedding data leads to covering image distortion and visual quality resulting in data security detection. A trade-off between robustness, imperceptibility, and embedded capacity is difficult to achieve with current algorithms due to limitations in their ability. Keeping this purpose insight, an improved reversibility watermarking methodology is proposed to maximize data embedding capacity and imperceptibility while maintaining data security as a primary concern. A key is generated by a random path with minimum bit flipping is selected in the 4 × 4 block to gain access to the data embedding patterns. The random path's complex structure ensures data security. Data of various sizes (8 KB, 16 KB, 32 KB) are used to analyze image imperceptibility and evaluate quality factors. The proposed reversible watermarking methodology performance is tested under standard structures PSNR, SSIM, and MSE. The results revealed that the MRI watermarked images are imperceptible, like the cover image when LSB is 3 bits plane. Our proposed reversible watermarking methodology outperforms other related techniques in terms of average PSNR (49.29). Experiment results show that the suggested reversible watermarking method improves data embedding capacity and imperceptibility compared to existing state-of-the-art approaches.

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“…Various statistical measures are applied to verify the imperceptibility of the cover medium. Statistical scoring works best for secret textual information compared to similar existing techniques [31]. Biometric systems face many security and data integrity challenges.…”

Section: Related Workmentioning

confidence: 99%

A Dynamic Three-Bit Image Steganography Algorithm for Medical and e-Healthcare Systems

et al. 2020

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Massive advances in internet infrastructure are impacting e-healthcare services compared to conventional means. Therefore, extra care and protection is needed for extremely confidential patient medical records. With this intention, we have proposed an enhanced image steganography method, to improve imperceptibility and data hiding capacity of stego images. The proposed Image Region Decomposition (IRD) method, embeds more secret information with better imperceptibility, in patient's medical images. The algorithm decomposes the grayscale magnetic resonance imaging (MRI) images into three unique regions: low-intensity, medium-intensity, and high-intensity. Each region is made up of k number of pixels, and in each pixel we operate the block of n least significant bits (LSBs), where 1 ≤ n ≤ 3. Four classes of MRI images of different dimensions are used for embedding. Data with different volumes are used to test the images for imperceptibility and verified with quality factors. The proposed IRD algorithm is tested for performance, on the set of brain MRI images using peak signal-to-noise ratio (PSNR), mean square error (MSE) and structural similarity (SSIM) index. The results elucidated that the MRI stego image is imperceptible, like the original cover image by adjusting 2 nd and 1 st LSBs in the low-intensity region. Our proposed steganography technique provides a better average PSNR (49.27), than other similar methods. The empirical results show that the proposed IRD algorithm, significantly improves the imperceptibility and data embedding capacity, compared to the existing state-of-the-art methods.

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Steganographic on Pixel Value Differencing in Iris Biometric

Cited by 5 publications

References 5 publications

Dynamic 8-bit XOR algorithm with AES crypto algorithm for image steganography

Dynamic 8-bit XOR algorithm with AES crypto algorithm for image steganography

A Robust Data Hiding Reversible Technique for Improving the Security in e-Health Care System

A Dynamic Three-Bit Image Steganography Algorithm for Medical and e-Healthcare Systems

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