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<p>The safety of sensitive information on the way to the destination becomes an area of increasing concern, especially in areas such as healthcare and financial sectors. There is an emergency necessity of ensuring the optimized and safe infrastructure of information interchange. The issue that is discussed in this research is data transmission security by applying an effective steganographic option. The research shows FIEO Optimal Location Enabled Stegochain as an innovative framework that assumes the combination of steganography with FIEO algorithm to find the safest locations places of embeddings in the image. The method guarantees strong embedding and extraction of data because of Discrete Wavelet Transform (DWT) and its reverse (IDWT). The proposed model is more secure, has a reduced data distortion and correlation and Peak Signal-to-Noise Ratio (PSNR) compared to the current methods. The robustness and the effectiveness of the proposed method are validated by the PSNR values which have been 64.297 in the case of random noise and 61.288 in the salt-and-pepper noise condition as analysed in the experiment as well as correlation coefficients which are 0.81 and 0.79 respectively under random noise and salt-and-pepper noise conditions.</p>

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A secure framework for optimized data transmission using steganographic techniques

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月27日

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  • Priya Batta,
  • Abhishek Kumar,
  • Pramod Singh Rathore

摘要

The safety of sensitive information on the way to the destination becomes an area of increasing concern, especially in areas such as healthcare and financial sectors. There is an emergency necessity of ensuring the optimized and safe infrastructure of information interchange. The issue that is discussed in this research is data transmission security by applying an effective steganographic option. The research shows FIEO Optimal Location Enabled Stegochain as an innovative framework that assumes the combination of steganography with FIEO algorithm to find the safest locations places of embeddings in the image. The method guarantees strong embedding and extraction of data because of Discrete Wavelet Transform (DWT) and its reverse (IDWT). The proposed model is more secure, has a reduced data distortion and correlation and Peak Signal-to-Noise Ratio (PSNR) compared to the current methods. The robustness and the effectiveness of the proposed method are validated by the PSNR values which have been 64.297 in the case of random noise and 61.288 in the salt-and-pepper noise condition as analysed in the experiment as well as correlation coefficients which are 0.81 and 0.79 respectively under random noise and salt-and-pepper noise conditions.