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Double graph correlation encryption based on hyperchaos.

Luoyin Feng1, Jize Du2, Chong Fu1

  • 1School of Computer Science and Engineering, Northeastern University, Shenyang, China.

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Summary
This summary is machine-generated.

This study introduces a novel chaos theory-based encryption method for enhanced data security. The new approach significantly reduces data correlation and improves resistance against various cyberattacks.

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Area of Science:

  • Information Security
  • Applied Mathematics
  • Cryptography

Background:

  • Data security is paramount, with encryption being a primary defense.
  • Increasing computational power and AI necessitate advanced encryption strategies.
  • Existing encryption methods struggle against sophisticated threats.

Purpose of the Study:

  • To present a novel two-way information encryption approach utilizing chaos theory.
  • To introduce a new chaos model with enhanced key space and sensitivity.
  • To improve data security against modern computational and AI-driven attacks.

Main Methods:

  • Developed a new chaos model exhibiting superior chaotic behavior and key space.
  • Implemented a multi-stage encryption process involving byte vector conversion, diffusion, and permutation.
  • Utilized an iterative reversible rule-based model for final diffusion to reduce data correlation.

Main Results:

  • Reduced data correlation by at least 28.57% compared to previous methods.
  • Achieved at least 14.15% increase in Mean Squared Error (MSE) and 1.79% in Bit Error Rate (BER).
  • Demonstrated high resistance to attacks with key sensitivity of 10^-28 and average entropy of 7.9993.

Conclusions:

  • The proposed chaos-based encryption method offers a robust solution for securing sensitive data.
  • The strategy effectively reduces data correlation and enhances resistance to brute-force, statistical, and differential attacks.
  • This advanced encryption technique is suitable for various data types, including images, text, and audio.