A memristive superchaotic conservative system and image encryption on DNA coding and parallel computing

This paper presents a novel memristive hyperchaotic conservative system and develops an advanced image encryption scheme integrating the proposed system with DNA coding and parallel computing. The key contributions and findings are summarized as follows: First, a hyperchaotic system is innovatively designed by embedding a memristor into a conservative system framework. Second, comprehensive theoretical analyses are conducted to examine the system’s stability and conservative characteristics, with specific stability conditions being mathematically derived. Third, the system’s dynamic properties are thoroughly investigated through multiple analytical tools, including Lyapunov exponent analysis, bifurcation diagrams, phase portraits, and spectrograms, revealing remarkable symmetry characteristics and superior randomness properties. Finally, an innovative image encryption scheme is developed, leveraging DNA coding for enhanced security and parallel computing for improved efficiency. The DNA-based encryption mechanism demonstrates robust security features, as validated through comprehensive statistical analyses and various attack simulations. The parallel computing architecture significantly boosts computational speed, enabling real-time encryption and decryption operations. Numerical simulations confirm the superior security performance and exceptional encryption/decryption speed of the proposed scheme, demonstrating its potential for practical applications in secure image transmission and storage.

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Publication Details

Journal
Modern Physics Letters B
Published
2025-10-15
DOI
https://doi.org/10.1142/s0217984925502483
Primary Topic
Chaos-based Image/Signal Encryption
Type
article
Field-Weighted Citation Impact
0.00
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article

A memristive superchaotic conservative system and image encryption on DNA coding and parallel computing

Zongli Yang, Li Zhang, Dawei Ding, Chuan Liu et al.
Modern Physics Letters B
Chaos-based Image/Signal Encryption
article

A memristive superchaotic conservative system and image encryption on DNA coding and parallel computing

Zongli Yang, Li Zhang, Dawei Ding, Chuan Liu, X. Pu
article en

Abstract

This paper presents a novel memristive hyperchaotic conservative system and develops an advanced image encryption scheme integrating the proposed system with DNA coding and parallel computing. The key contributions and findings are summarized as follows: First, a hyperchaotic system is innovatively designed by embedding a memristor into a conservative system framework. Second, comprehensive theoretical analyses are conducted to examine the system’s stability and conservative characteristics, with specific stability conditions being mathematically derived. Third, the system’s dynamic properties are thoroughly investigated through multiple analytical tools, including Lyapunov exponent analysis, bifurcation diagrams, phase portraits, and spectrograms, revealing remarkable symmetry characteristics and superior randomness properties. Finally, an innovative image encryption scheme is developed, leveraging DNA coding for enhanced security and parallel computing for improved efficiency. The DNA-based encryption mechanism demonstrates robust security features, as validated through comprehensive statistical analyses and various attack simulations. The parallel computing architecture significantly boosts computational speed, enabling real-time encryption and decryption operations. Numerical simulations confirm the superior security performance and exceptional encryption/decryption speed of the proposed scheme, demonstrating its potential for practical applications in secure image transmission and storage.

Modern Physics Letters BVol. 39(36)
Anhui University (CN)
Openalex Percentile: Top 71%
Chaos-based Image/Signal Encryption
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A memristive superchaotic conservative system and image encryption on DNA coding and parallel computing — Zongli Yang, Li Zhang, et al. · Modern Physics Letters B (2025) | TGRS Research Map | TGRS