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Genetic algorithm and hamilton path based data hiding scheme including embedding cost optimization

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Abstract

Steganography is used at a large scale in various security systems. It is the science and art of hiding secret information into data. Various steganography schemes have been proposed over the years, but most of them are not promising enough to provide a large capacity of embedding and visually prevent the image’s degradation. Histograms can reveal the existence of secret information, and it is also an essential issue in the security of the data. In this Paper, the main objective is to reduce the bit-flip cost count and maximize the PSNR value to reduce the image distortion and keep the data secure by using secret keys while embedding. In this proposed paper, the genetic algorithm (GA) is employed to select the best chromosome that has the minimum bit-flip cost count and maximum PSNR. Data security is achieved by the secret key generated from Hamiltonian path for embedding and retrieving of data. The proposed technique is robust against steganographic attacks and even if presence of data is observed it not possible to guess the embedding pattern. The result section demonstrates that the proposed technique outperform the existing techniques by increasing the PSNR significantly by approx 7 percent that lead to the increase in PSNR value up to 41.8dB for three bit per pixel embedding.

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Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Information Technology, Rajasthan, India

    Gyan Singh Yadav, Parth Mangal, Gaurav Parmar & Shubham Soliya

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  1. Gyan Singh Yadav
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  2. Parth Mangal
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  3. Gaurav Parmar
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  4. Shubham Soliya
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Correspondence to Gyan Singh Yadav.

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Yadav, G.S., Mangal, P., Parmar, G. et al. Genetic algorithm and hamilton path based data hiding scheme including embedding cost optimization. Multimed Tools Appl 82, 20233–20249 (2023). https://doi.org/10.1007/s11042-022-14322-9

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  • DOI: https://doi.org/10.1007/s11042-022-14322-9

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