Optimize Image Steganography Based on Distinction Disparity Value and HMPSO to Ensure Confidentiality and Integrity DOI Creative Commons
Ali Salem Ali, Suray Alsamaraee, Aya Ayad Hussein

и другие.

Journal of Computer Networks and Communications, Год журнала: 2024, Номер 2024(1)

Опубликована: Янв. 1, 2024

To secure the massive amounts of secret messages, integrity and confidentiality challenges must be addressed. Pressing in context a steganography system include security, imperceptibility, capacity issues. There are trade‐offs between payload security that have been neglected by researchers, as fixing one issue has indicated to affect other, vice versa. overcome these challenges, new scheme based on HMPSO DDV was introduced. The is short for Hénon map particle swarm optimization, while distinction disparity value. proposed consisted four phases with different contributions. first phase used preprocess messages cover images. In this phase, message compressed using Huffman method. second involved embedding procedure. This consists two contributions DDV. responsible optimal pixels’ selection. While process. third involves extraction extraction, reverse processes previous steps implemented. Different evaluation parameters validate test such SSIM, PSNR, HVS, Histogram analysis, chi‐square test. Based findings, solved provides robust system.

Язык: Английский

Optimize Image Steganography Based on Distinction Disparity Value and HMPSO to Ensure Confidentiality and Integrity DOI Creative Commons
Ali Salem Ali, Suray Alsamaraee, Aya Ayad Hussein

и другие.

Journal of Computer Networks and Communications, Год журнала: 2024, Номер 2024(1)

Опубликована: Янв. 1, 2024

To secure the massive amounts of secret messages, integrity and confidentiality challenges must be addressed. Pressing in context a steganography system include security, imperceptibility, capacity issues. There are trade‐offs between payload security that have been neglected by researchers, as fixing one issue has indicated to affect other, vice versa. overcome these challenges, new scheme based on HMPSO DDV was introduced. The is short for Hénon map particle swarm optimization, while distinction disparity value. proposed consisted four phases with different contributions. first phase used preprocess messages cover images. In this phase, message compressed using Huffman method. second involved embedding procedure. This consists two contributions DDV. responsible optimal pixels’ selection. While process. third involves extraction extraction, reverse processes previous steps implemented. Different evaluation parameters validate test such SSIM, PSNR, HVS, Histogram analysis, chi‐square test. Based findings, solved provides robust system.

Язык: Английский

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