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Secure and Embedded Processing Framework for Payload Scattering in Image Steganography with Low Computation Time

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Abstract

Generally, irreversible and reversible image steganography use the concept of encryption to produce a higher level of security. In this case, the payload is encrypted before embedding in the medium cover. However, it has more complexity if the size of the payload is high. Therefore, such a technique is required, which would be less complex and more secure than any of the existing encryption algorithms, even if the size of the payload is large. This paper possesses such an approach with the concept of payload Scattering. In the proposed approach payload is distributed into three components with the help of the primary cover image. The decomposed components are then embedded into RGB secondary cover image. The proposed approach eliminates the need for encryption and reduces the system’s complexity in payload design. It has been observed with the result that the distortion in the decomposed components SMap, EFactor and NError, has been significant enough to hide the payload. It has a deficient computation time compared with existing encryption algorithms. Therefore, the proposed method based on an embedded processing framework can be considered as the best alternative to the encryption algorithm to conceal the payload with low computation time as well as independence in the size of the payload.

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Source: http://sipi.usc.edu/services/Miscellaneous (standard image dataset)

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Data sharing does not apply to this article as no datasets were generated or analyzed during the current study.

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  1. Department of Computer Engineering and Applications, GLA Unversity, Mathura, 281406, India

    Sandeep Rathor, Subhash Chand Agrawal, Robin Singh Bhadoria & Praphula Kumar Jain

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  1. Sandeep Rathor
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  2. Subhash Chand Agrawal
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  3. Robin Singh Bhadoria
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  4. Praphula Kumar Jain
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Rathor, S., Agrawal, S.C., Bhadoria, R.S. et al. Secure and Embedded Processing Framework for Payload Scattering in Image Steganography with Low Computation Time. Wireless Pers Commun 130, 2679–2695 (2023). https://doi.org/10.1007/s11277-023-10398-0

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