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CNNHSIE: CNN and hyperchaotic-based image encryption algorithm using high-speed permutation and dynamic diffusion

delete2026-09-08
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PRE
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E
Ebrahim Zarei Zefreh *
M
Mohammad Heydari
DOI:10.1007/s00521-026-12419-ydelete
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Abstract

Abstract

En 中文
The exponential increase in sharing images on digital platforms, including in areas such as military, medical, and financial applications, and the potential risks of unauthorized access and manipulation, highlights the urgent need for effective and secure image encryption. This paper introduces Convolutional Neural Network and Hyperchaotic System-based Image Encryption (CNNHSIE), a new high-speed, reliable, and secure scheme for image encryption. CNNHSIE is based on the hyperchaotic system to generate a random matrix, as well as a novel high-speed permutation technique called HSPT and a dynamic pixel diffusion technique called DPDT. Additionally, the proposed technique incorporates convolutional neural networks to improve security and efficiency. The VGG16 model is used to compute the public key based on the features extracted from the plain image. The CNNHSIE was thoroughly evaluated using various analysis techniques on the USC-SIPI database and other public datasets from sources including Radiopaedia and Kaggle. It is characterized by high key sensitivity, the ability to resist various attacks and high performance. For the “Male" image 1024 $$\times$$ 1024, CNNHSIE achieves, a UACI value of 33.4809%, an NPCR value of 99.6140%, near-zero correlation, an entropy of 7.9998, and encryption time of 0.1216 seconds. The combination of strong security and high performance makes CNNHSIE a promising candidate for secure, practical and real-time image encryption and communication applications.
Keywords:
Image encryption
CNN
Hyperchaotic system
Permutation
Diffusion

Journal

Neural Computing and Applications cover
Neural Computing and Applications
IF:
4.5
Papers:
855
Citations:
3.2W

Organization

D
department of computer science
Scholars:
796
Papers: 416
Citations: 0
Cited Papers

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