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<p>This paper presents a novel image encryption method combining neural networks, color space transformation, and chaotic systems. Unlike traditional methods, it enhances the dimensionality of complexity by introducing key- and input-dependent security. It integrates dual-stage pixel scrambling, memory-based bidirectional substitution, and color transformation neural networks. The proposed method yields low adjacent pixel correlation (0.0002) and near-ideal entropy (7.9990), with minimal computational load.</p>

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Image Encryption using Color Space Neural Network Transformation and Chaotic Pixel Perturbation

  • 期刊论文

  • 发表日期：

    2025年6月18日

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  • Muhammed Al-Muhammed,
  • Ahmad Ababneh,
  • Ahmad Al-Daraiseh

摘要

This paper presents a novel image encryption method combining neural networks, color space transformation, and chaotic systems. Unlike traditional methods, it enhances the dimensionality of complexity by introducing key- and input-dependent security. It integrates dual-stage pixel scrambling, memory-based bidirectional substitution, and color transformation neural networks. The proposed method yields low adjacent pixel correlation (0.0002) and near-ideal entropy (7.9990), with minimal computational load.