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An Image Encryption Algorithm Based on Random Hamiltonian Path.

Wei Zhang1, Shuwen Wang1, Weijie Han1

  • 1Software College, Northeastern University, No.11, Lane 3, Wenhua Road, Shenyang 110819, China.

Entropy (Basel, Switzerland)
|December 8, 2020
PubMed
Summary
This summary is machine-generated.

Researchers developed a novel image encryption method using random Hamiltonian paths to permute pixel bits and grey levels. This technique enhances security by shuffling data distribution and improving correlation coefficient analysis for stricter evaluations.

Keywords:
Bernoulli mapHamiltonian pathchaotic systemimage encryption

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Area of Science:

  • Computer Science
  • Cryptography
  • Graph Theory

Background:

  • Image encryption is crucial for data security.
  • Permutation and substitution are common techniques in image ciphers.
  • Hamiltonian paths offer a novel approach to data shuffling.

Purpose of the Study:

  • To propose a new bit-level image encryption scheme.
  • To utilize random Hamiltonian paths for image permutation.
  • To enhance the security and evaluation of image encryption algorithms.

Main Methods:

  • Generating random Hamiltonian paths within digital images.
  • Applying Hamiltonian paths across bit planes for pixel bit shuffling.
  • Using an adjusted Bernoulli map to ensure Hamiltonian path randomness.
  • Implementing a substitution method for pixel grey levels.

Main Results:

  • A novel bit-level image encryption scheme was successfully devised.
  • The proposed scheme demonstrated fair performance in simulations.
  • A flaw in the traditional correlation coefficient calculation for adjacent pixels was identified.
  • An enhanced correlation coefficient calculation provides a stricter encryption evaluation criterion.

Conclusions:

  • Random Hamiltonian paths offer an effective method for image permutation in encryption.
  • The adjusted Bernoulli map ensures the randomness of generated paths.
  • The enhanced correlation coefficient metric improves the assessment of encryption algorithms.