A Review on Medical Image Compression and Encryption Using Compressive Sensing

Saber, Hozan Kareem; Shakir, Mohammed Ahmed

doi:10.1109/csase51777.2022.9759638

Cited by 4 publications

(1 citation statement)

References 16 publications

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“…In [4], Natsheh et al introduced a selective encryption approach to secure medical images in DICOM format, which selects regions within medical images automatically using the pixel thresholding segmentation technique, and then uses different algorithms to compress and encrypt them according to their importance, so as to reduce the processing time. Medical image encryption can be accomplished by incorporating various techniques, such as chaos [5][6][7][8], DNA computing [9][10][11], wavelet transform [12][13][14], memristor [15,16], elliptic curve [17,18], compressed sensing [19,20] and deep learning [21,22].…”

Section: Introductionmentioning

confidence: 99%

3D medical image encryption algorithm using biometric key and cubic S-box

Liu,

Xue

2024

Phys. Scr.

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Considering the scarcity of research on 3D medical image encryption, this paper proposes a novel 3D medical image encryption scheme based on biometric key and cubic S-box. To enhance the data security, biometric keys are utilized to overcome the limitations of traditional methods where secret keys with no practical meaning, fixed length, and finite key space, while cubic S-box is constructed to increase the nonlinearity of image cryptosystem. The proposed cryptosystem mainly consists of four phases: pseudo-random sequence generation, confusion, substitution, and diffusion. Firstly, the stepwise iterative algorithm based on coupled chaotic systems is utilized for generating pseudo-random sequences for confusion and diffusion. Secondly, the confusion algorithm based on multiple sorting can scramble pixel positions in 3D images. Thirdly, guided by the designed cubic S-box, pixel substitution is executed sequentially. Lastly, the diffusion algorithm based on ECA and finite field multiplication is capable of increasing the plaintext sensitivity of cryptosystem by concealing the statistical characteristics of plaintext. Simulation experiments performed on multiple 3D medical images demonstrate that the proposed encryption scheme exhibits favorable statistical performance, sufficiently large key space, strong system sensitivity and robustness, and can resist various typical cryptographic attacks.

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