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<p>Based on the Li-Yorke theorem, we present two novel 1D discrete chaotic systems and develop an image encryption scheme that integrates compressed sensing (CS). The framework first applies discrete wavelet transform for plaintext sparsification, then permutes the sparse coefficients via Arnold transform, and compresses them with chaotic system-generated measurement matrices. Final diffusion encryption produces ciphertext images, with chaotic system parameters derived from plaintext as keys. Experiments demonstrate both superior reconstruction accuracy and robustness against chosen-plaintext/statistical attacks. The scheme shows promise for secure multimedia transmission in bandwidth-limited scenarios like Internet of Things (IoT) while meeting storage security requirements.</p>

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A chaotic system compressed sensing image scheme for information security

  • 期刊论文

  • 发表日期：

    2025年5月19日

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  • Luyuan Bai,
  • Hongyan Zang,
  • Xinyuan Wei

摘要

Based on the Li-Yorke theorem, we present two novel 1D discrete chaotic systems and develop an image encryption scheme that integrates compressed sensing (CS). The framework first applies discrete wavelet transform for plaintext sparsification, then permutes the sparse coefficients via Arnold transform, and compresses them with chaotic system-generated measurement matrices. Final diffusion encryption produces ciphertext images, with chaotic system parameters derived from plaintext as keys. Experiments demonstrate both superior reconstruction accuracy and robustness against chosen-plaintext/statistical attacks. The scheme shows promise for secure multimedia transmission in bandwidth-limited scenarios like Internet of Things (IoT) while meeting storage security requirements.