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      Exploiting Dynamic Vector-Level Operations and a 2D-Enhanced Logistic Modular Map for Efficient Chaotic Image Encryption

      , , , , , , ,
      Entropy
      MDPI AG

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          Abstract

          Over the past few years, chaotic image encryption has gained extensive attention. Nevertheless, the current studies on chaotic image encryption still possess certain constraints. To break these constraints, we initially created a two-dimensional enhanced logistic modular map (2D-ELMM) and subsequently devised a chaotic image encryption scheme based on vector-level operations and 2D-ELMM (CIES-DVEM). In contrast to some recent schemes, CIES-DVEM features remarkable advantages in several aspects. Firstly, 2D-ELMM is not only simpler in structure, but its chaotic performance is also significantly better than that of some newly reported chaotic maps. Secondly, the key stream generation process of CIES-DVEM is more practical, and there is no need to replace the secret key or recreate the chaotic sequence when handling different images. Thirdly, the encryption process of CIES-DVEM is dynamic and closely related to plaintext images, enabling it to withstand various attacks more effectively. Finally, CIES-DVEM incorporates lots of vector-level operations, resulting in a highly efficient encryption process. Numerous experiments and analyses indicate that CIES-DVEM not only boasts highly significant advantages in terms of encryption efficiency, but it also surpasses many recent encryption schemes in practicality and security.

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          Most cited references46

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          SOME BASIC CRYPTOGRAPHIC REQUIREMENTS FOR CHAOS-BASED CRYPTOSYSTEMS

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            Estimation of the Kolmogorov entropy from a chaotic signal

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              Cosine-transform-based chaotic system for image encryption

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                Author and article information

                Contributors
                Journal
                ENTRFG
                Entropy
                Entropy
                MDPI AG
                1099-4300
                August 2023
                July 31 2023
                : 25
                : 8
                : 1147
                Article
                10.3390/e25081147
                37628177
                de6b3e43-3f25-44ae-a0a0-21798f73b3ed
                © 2023

                https://creativecommons.org/licenses/by/4.0/

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