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<p>This study presents a sophisticated encryption methodology specifically designed for the secure transfer of medical images across cloud services. The initial phase of the algorithm involves the consolidation of multiple images to form a single augmented image, which is then subjected to the first layer of encryption. This layer employs an encryption key and an S-box generated through a Memristive Coupled Neural Network Model (MCNNM), establishing a strong foundation for security. Following this, the novel integration of Moore’s Automaton with Gold sequences is applied as a confusion mechanism, intrinsically scrambling the image structure to effectively disrupt pixel correlations. The encryption process iterates over <i>N</i> cycles, significantly deepening the level of encryption with each iteration. Performance evaluations reflect a considerable key space of <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(2^{2020}\)</EquationSource> </InlineEquation> and a high encryption rate of 15.5 Mbps, while rigorous statistical tests validate the algorithm’s resilience. The encryption system proposed in this manuscript not only ensures a formidable level of security but is also pragmatically designed for application in the protection of sensitive healthcare data.</p>

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Hyperchaos and the fusion of Moore’s automaton with gold sequences for augmented medical image encryption

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月12日

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  • Mohamed Gabr,
  • Eyad Mamdouh,
  • Dina El-Damak,
  • Minar El-Aasser,
  • Wassim Alexan,
  • Amr Aboshousha

摘要

This study presents a sophisticated encryption methodology specifically designed for the secure transfer of medical images across cloud services. The initial phase of the algorithm involves the consolidation of multiple images to form a single augmented image, which is then subjected to the first layer of encryption. This layer employs an encryption key and an S-box generated through a Memristive Coupled Neural Network Model (MCNNM), establishing a strong foundation for security. Following this, the novel integration of Moore’s Automaton with Gold sequences is applied as a confusion mechanism, intrinsically scrambling the image structure to effectively disrupt pixel correlations. The encryption process iterates over N cycles, significantly deepening the level of encryption with each iteration. Performance evaluations reflect a considerable key space of \(2^{2020}\) and a high encryption rate of 15.5 Mbps, while rigorous statistical tests validate the algorithm’s resilience. The encryption system proposed in this manuscript not only ensures a formidable level of security but is also pragmatically designed for application in the protection of sensitive healthcare data.