Exploiting 2D-SDMCHM and matching embedding driven by flag-shaped hexagon prediction for visually meaningful medical image cryptosystem

Chai, Xiuli; Shang, Guangyu; Wang, Binjie; Gan, Zhihua; Zhang, Wenkai

doi:10.1016/j.chaos.2024.115153

Chaos, Solitons & Fractals

2024

DOI: 10.1016/j.chaos.2024.115153

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Exploiting 2D-SDMCHM and matching embedding driven by flag-shaped hexagon prediction for visually meaningful medical image cryptosystem

Xiuli Chai,

Guangyu Shang,

Binjie Wang

et al.

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2024

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Cited by 3 publications

References 55 publications

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Dual medical image watermarking using SRU-enhanced network and EICC chaotic map

Yan,

Wang,

Hirota

2024

Complex Intell. Syst.

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Dual medical image watermarking using SRU-enhanced network and EICC chaotic map

Yan,

Wang,

Hirota

2024

Complex Intell. Syst.

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Image compression encryption algorithm combining two-dimensional modular hyperchaotic map and compressed sensing

Yin,

Xu,

Zhang

et al. 2024

Phys. Scr.

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Recently, to offer better ensure for image privacy security, numerous new image encryption algo-rithms have been proposed. However, these algorithms still suffer from the problems of chaotic per-formance scarcity, low encryption effect, and high consumption of computational resources. To solve the above issues, we first construct a two-dimensional modular hyperchaotic map (2D-MHM). Then, we further develop an image encryption algorithm based on 2D-MHM and compressed sensing (CS). Several chaotic metrics verify the randomness and validity of 2D-MHM. These metrics include bi-furcation diagram, Lyapunov exponent, initial value sensitivity, 0-1 test, and NIST test. Specifically, CS significantly reduces the ciphertext image size thereby reducing its resource consumption during transmission. Reality-preserving fractional DCT (RP-Fdct) diffusion is utilized to transform pixels into the frequency domain to enhance the encryption effect. Subsequently, lightweight index confu-sion and XOR diffusion further improve the algorithm security. The security of the algorithm is veri-fied through various experiments. It is able to encrypt grayscale and color images of different sizes with good results. Notably, this algorithm also implements the encryption requirements for binary images. Due to our designs, it outperforms recently reported encryption algorithms in several areas, especially in reconstruction performance.

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An Innovative Algorithm Based on Chaotic Maps Amalgamated with Bit-Level Permutations for Robust S-Box Construction and Its Application in Medical Image Privacy

Hazzazi,

Baowidan,

Yousaf

et al. 2024

Symmetry

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Data security and privacy have become essential due to the increasingly advanced interconnectivity in today’s world, hence the reliance on cryptography. This paper introduces a new algorithm that uses a novel hybrid Tent–May chaotic map to generate pseudo-random numbers, as well as block encryption. We design a robust S-box by combining the Tent and May Maps, which yields a chaotic system with improved cryptographic properties. This S-box is a critical cryptographic primitive that significantly improves encryption security and leverages the strengths of both maps. The encryption process involves two key steps: block-wise substitution and permutation. First, we divide the image into 16×16 blocks, then substitute each pixel with the 8−byte key and S-box. Next, we convert the encrypted image back into vector form, reorganize it using the permutation vector based on the subgroups of S16, and finally return it to its original form. This approach greatly improves block cipher security when used, especially to protect medical images by guaranteeing their confidentiality and noninterference. Performance measures like PSNR, UACI, MSE, NCC, AD, SC, MD, and NAE prove how immune our method is to various cryptographic and statistical attacks, making it more accurate and more secure than the existing techniques.

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Exploiting 2D-SDMCHM and matching embedding driven by flag-shaped hexagon prediction for visually meaningful medical image cryptosystem

Cited by 3 publications

References 55 publications

Dual medical image watermarking using SRU-enhanced network and EICC chaotic map

Dual medical image watermarking using SRU-enhanced network and EICC chaotic map

Image compression encryption algorithm combining two-dimensional modular hyperchaotic map and compressed sensing

An Innovative Algorithm Based on Chaotic Maps Amalgamated with Bit-Level Permutations for Robust S-Box Construction and Its Application in Medical Image Privacy

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