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<p>The fast growth of Internet of Things (IoT) devices requires secure and lightweight image encryption methods. This study introduces the hybrid HLCAC cipher, which combines one-dimensional Cellular Automata (CA), chaotic maps, and a zigzag transform. CA enables fast, low-cost parallel operations; chaotic maps add strong key sensitivity; and the zigzag transform breaks pixel patterns, improving diffusion and confusion. This study tests the performance of HLCAC on the standard Peppers image. The encrypted image achieves an entropy of 7.9968, which is close to the ideal value of 8, proving a uniform pixel distribution. The NPCR of 99.62% and UACI of 49.93% confirm strong resistance to differential attacks. A PSNR of 9.12 dB and an MSE of 4113 demonstrate that encryption strongly distorts the image, preventing recovery of the original without the key. Correlation analysis yields values close to zero, indicating that the encrypted image hides all visual details of the original. This study presents an original design that, for the first time, combines CA, chaotic maps, and a zigzag transform to provide a secure and lightweight encryption model for protecting IoT images.</p>

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HLCAC: hybrid lightweight cipher for image encryption in IoT applications using 1D cellular automata and chaotic maps with zigzag transform

  • 期刊论文

  • 发表日期：

    2026年7月14日

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  • Biswarup Yogi,
  • Ajoy Kumar Khan

摘要

The fast growth of Internet of Things (IoT) devices requires secure and lightweight image encryption methods. This study introduces the hybrid HLCAC cipher, which combines one-dimensional Cellular Automata (CA), chaotic maps, and a zigzag transform. CA enables fast, low-cost parallel operations; chaotic maps add strong key sensitivity; and the zigzag transform breaks pixel patterns, improving diffusion and confusion. This study tests the performance of HLCAC on the standard Peppers image. The encrypted image achieves an entropy of 7.9968, which is close to the ideal value of 8, proving a uniform pixel distribution. The NPCR of 99.62% and UACI of 49.93% confirm strong resistance to differential attacks. A PSNR of 9.12 dB and an MSE of 4113 demonstrate that encryption strongly distorts the image, preventing recovery of the original without the key. Correlation analysis yields values close to zero, indicating that the encrypted image hides all visual details of the original. This study presents an original design that, for the first time, combines CA, chaotic maps, and a zigzag transform to provide a secure and lightweight encryption model for protecting IoT images.