A Secured Steganography Algorithm for Hiding an Image in an Image

Kini, Gopalakrishna N; Kini, Vishwas G.; Gautam, .

doi:10.1007/978-981-10-8797-4_54

Cited by 20 publications

(7 citation statements)

References 4 publications

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“…As we have considered colour animated sequence, in RGB format, for embedding and we know every pixel of a colour image frame contains 3 channels -Red, Green and Blue. Moreover, it is well reported that green component of a pixel is very sensitive to human vision and hence we have considered only the red and blue channel for data embedding [25]. This consideration helps to improve the imperceptibility of the stego media.…”

Section: Embedding Processmentioning

confidence: 99%

A Non-Sequential Approach for Steganography using Perfect Square Quotient Differencing (NSPSQD)

Basak

Chatterjee

Das

et al. 2022

Preprint

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Data security is considered as one of the prime concerns in digital communication era. Steganography and cryptography are two parallel approaches adopted for protecting such data. Steganography camouflages the secret data into a cover media while cryptography converts it into an unreadable format. In this paper, we propose a non-sequential steganographic scheme by employing Perfect Square Quotient Differencing, where the secret data is embedded non-sequentially in two parallel phases on the two counter parts of a pixel, quotient and remainder. In phase-I, we apply Two Least Significant Bit (2LSB) replacement on the remainder part whereas perfect square quantization is applied on the quotient part in phase-II. A new format of range-table has been introduced to estimate the length of the embedding bits in phase-II. The proposed method secures high embedding capacity (on an average 3bpp) due to 2-phases of embedding at every single pixel. The proposed algorithm has been experimented on a large set of color animated image sequences. To establish the algorithmic efficiency, Peak Signal to Noise Ratio, Mean Square Error, Universal Image Quality Index and Payload Curve have been used as performance measure. The proposed method outperforms in all performance measure as compared with few modern steganography methods. Steganalysis have also been carried out to establish the robustness and security of the proposed against various security threats. Proposed algorithm can be used to protect digital documents in cloud based storage platform.

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Section: Embedding Processmentioning

confidence: 99%

A Non-Sequential Approach for Steganography using Perfect Square Quotient Differencing (NSPSQD)

Basak

Chatterjee

Das

et al. 2022

Preprint

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“…Some researchers experiment with the type of data hidden within the image. The most common secret data types in image steganography are text [8] and images [1]. On the other hand, to protect copyrights and provide a form of digital signatures, watermarking techniques are used.…”

Section: Literature Reviewmentioning

confidence: 99%

“…By definition, the histogram of a given image is a graphical representation of the number of pixels in that image as a function of their intensity. In other words, the image histogram provides a graphical depiction of the general color distribution within the image [1]. Thus, when the image elements are changed, this change is reflected in the shape of the histogram.…”

Section: Histogram Analysismentioning

confidence: 99%

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Increasing Participants Using Counting-Based Secret Sharing via Involving Matrices and Practical Steganography

Al-Shaarani

Gutub

2021

Arab J Sci Eng

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Secret sharing is an approach for accessing sensitive information by several authorized participants. It shares the secret key in different forms among several authorized participants, where a certain number of which is required to retrieve the original secret. This secret sharing raised a new practicality challenge of human secrecy memorization as well as limited number of users allowed, which have been addressed within this work. This paper examines two particular secret sharing techniques known as the counting-based secret sharing and the matrix-based secret sharing, which enhances the former to accommodate a high number of participants. This work aimed to serve participants accommodating the share's memorization challenge via image steganography as well as testing both schemes in the cases of original 1-bit and 2-bit methods. We compared practicality applying the secret sharing methods combined with two image steganography methods: the least significant bit and the discrete wavelet transform. Our findings included interesting remarks regarding both security and robustness. Our results demonstrated that despite the large number of shares generated, as to serve more participants using the matrix-based scheme, its performance was highly satisfactory. Our experiments illustrated high imperceptibility levels for the matrix-based scheme, which in turn provides higher security and robustness compared to the original method, which provided very few shares serving a limited number of participants.

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“…If data are digital then it can be modified and transferred easily whenever and wherever required. However data are transferred on some communication channels, therefore protection of data is required for unauthorized access [1]. Moreover, information is also most pricey and precious.…”

Section: Introductionmentioning

confidence: 99%

Classification of Image Steganography in Substitution Technique

Vaidya

Kargathara

Kumbharana

2020

Rising Threats in Expert Applications and Solutions

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The science of communicating secret data using multimedia cover like audio, image, video files, etc. is called steganography. The technique steganography is used for hiding a secret data from unauthorized access or user. Steganography technique can be implemented using many different file formats, or in other words we can use different file formats as cover media but here we would talk about Digital Image-based Steganography for its obvious advantages. Also, we know that rapid and unimaginable developments in digital image processing methods make researcher work even more harder to achieve the ultimate objectives of steganography like robustness, security, resistance to different attacks, and payload capacity. The steganography method also confirms that the methodology or technique also increases the quality of the stego image keeping secure the secret data. The quality measures are PSNR and MSE. Through the following paper, we will study various states of art methods for steganography and compare the same so that it would be a great and ready reference material for the research scholars who are working on Digital Image Steganography.

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A Secured Steganography Algorithm for Hiding an Image in an Image

Cited by 20 publications

References 4 publications

A Non-Sequential Approach for Steganography using Perfect Square Quotient Differencing (NSPSQD)

A Non-Sequential Approach for Steganography using Perfect Square Quotient Differencing (NSPSQD)

Increasing Participants Using Counting-Based Secret Sharing via Involving Matrices and Practical Steganography

Classification of Image Steganography in Substitution Technique

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