An Advanced Image Encryption Algorithm Integrating Orthogonal Latin Square Transversal for Shuffling With Lorenz Chaotic System for Diffusion

ABSTRACT In this work, we introduce a new image encryption method designed to overcome key weaknesses found in many existing techniques—like low randomness, poor sensitivity to key changes, and vulnerability to statistical attacks. Our algorithm combines two powerful ideas: first, we use orthogonal Latin square transversals to shuffle pixels in a way that avoids repetition and boosts spatial unpredictability, and second, we apply a chaos‐based diffusion process using the Lorenz chaotic system to change pixel values, which makes the encryption highly sensitive to initial conditions and resistant to intrusion attempts. The two primary steps of the encryption process are pixel permutation using organized shuffling and diffusion using chaotic sequences produced by the Lorenz chaotic system. Standard grayscale images (256 × 256) were used to evaluate the method. Results of keyspace analysis, histogram analysis, correlation analysis, information entropy analysis, NPCR and UACI analysis, and key sensitivity analysis indicate strong and robust security of the algorithm against various kinds of attacks. It only took 0.1689 s to encrypt each image, demonstrating the method's efficiency and security. Our algorithm offers a dependable solution for safe image encryption since it is complicated, resilient, and resistant to statistical and differential assaults when compared with other methods.

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Publication Details

Journal
Security and Privacy
Published
2025-10-27
DOI
https://doi.org/10.1002/spy2.70128
Citations
1
Primary Topic
Chaos-based Image/Signal Encryption
Type
article
Field-Weighted Citation Impact
1.28
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An Advanced Image Encryption Algorithm Integrating Orthogonal Latin Square Transversal for Shuffling With Lorenz Chaotic System for Diffusion

Farhad Ansari, Piyush Kumar Singh, Rohitesh Pradhan, Pankaj Mishra et al.
1 citations
Security and Privacy
Chaos-based Image/Signal Encryption
1.28
article

An Advanced Image Encryption Algorithm Integrating Orthogonal Latin Square Transversal for Shuffling With Lorenz Chaotic System for Diffusion

Farhad Ansari, Piyush Kumar Singh, Rohitesh Pradhan, Pankaj Mishra, Vivek Kumar Jain, Bhawna Jha
article en
1 citations

Abstract

ABSTRACT In this work, we introduce a new image encryption method designed to overcome key weaknesses found in many existing techniques—like low randomness, poor sensitivity to key changes, and vulnerability to statistical attacks. Our algorithm combines two powerful ideas: first, we use orthogonal Latin square transversals to shuffle pixels in a way that avoids repetition and boosts spatial unpredictability, and second, we apply a chaos‐based diffusion process using the Lorenz chaotic system to change pixel values, which makes the encryption highly sensitive to initial conditions and resistant to intrusion attempts. The two primary steps of the encryption process are pixel permutation using organized shuffling and diffusion using chaotic sequences produced by the Lorenz chaotic system. Standard grayscale images (256 × 256) were used to evaluate the method. Results of keyspace analysis, histogram analysis, correlation analysis, information entropy analysis, NPCR and UACI analysis, and key sensitivity analysis indicate strong and robust security of the algorithm against various kinds of attacks. It only took 0.1689 s to encrypt each image, demonstrating the method's efficiency and security. Our algorithm offers a dependable solution for safe image encryption since it is complicated, resilient, and resistant to statistical and differential assaults when compared with other methods.

Security and PrivacyVol. 8(6)
Central University of South Bihar (IN)
Openalex Percentile: Top 15%
Chaos-based Image/Signal Encryption
1.28
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An Advanced Image Encryption Algorithm Integrating Orthogonal Latin Square Transversal for Shuffling With Lorenz Chaotic System for Diffusion — Farhad Ansari, Piyush Kumar Singh, et al. · Security and Privacy (2025) | TGRS Research Map | TGRS