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Asymmetric image encryption scheme based on the Quantum logistic map and cyclic modulo diffusion.

Guodong Ye1, Huishan Wu1, Kaixin Jiao1

  • 1Faculty of Mathematics and Computer Science, Guangdong Ocean University, Zhanjiang 524088, China.

Mathematical Biosciences and Engineering : MBE
|September 14, 2021
PubMed
Summary

This study introduces a novel asymmetric image encryption method using Rivest-Shamir-Adleman (RSA) and Arnold transformation. The technique enhances security against chosen-plaintext attacks through image-related keystream generation.

Keywords:
Arnold mapQuantum logistic mapend-to-start cyclic modulo diffusionimage encryption

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Area of Science:

  • Cryptography
  • Image Processing
  • Computer Science

Background:

  • Digital image security is crucial.
  • Existing encryption methods face challenges in resisting sophisticated attacks.
  • Asymmetric cryptography offers enhanced security features.

Purpose of the Study:

  • To propose a novel asymmetric image encryption scheme.
  • To enhance resistance against chosen-plaintext and known-plaintext attacks.
  • To improve the security and sensitivity of image encryption.

Main Methods:

  • Utilizing the Rivest-Shamir-Adleman (RSA) algorithm for initial value generation.
  • Applying Arnold transformation for initial image scrambling.
  • Implementing exclusive-OR (XOR) diffusion on rows and columns.
  • Employing cyclic modulo diffusion with an image-related keystream.

Main Results:

  • The proposed scheme effectively encrypts images using a combination of RSA and Arnold transformation.
  • The encryption process demonstrates strong plain sensitivity and key sensitivity.
  • The image-related keystream enhances resistance to chosen-plaintext and known-plaintext attacks.

Conclusions:

  • The developed asymmetric image encryption scheme offers a robust solution for secure image transmission.
  • The integration of RSA, Arnold transformation, and novel diffusion techniques provides high security.
  • The algorithm is effective in protecting sensitive image data.