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Bottom-boosting differential evolution based digital image security analysis
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AI
DOI：10.1016/j.jisa.2021.102811.png)
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Abstract
En 中文
With the advancements in multimedia applications, many images are transferred over public networks. Therefore, these images are prone to various security threats. Recently, many image encryption algorithms have been designed to secure the communication of digital images. Generally, hyperchaotic maps are utilized to generate the secret keys for encrypting the images. However, these maps suffer from the attribute tuning issue. Therefore, in this paper, six-dimensional hyperchaotic map (SHM) is tuned using bottom-boosting differential evolution. Entropy and correlation coefficient are used as a fitness function. The proposed map provides six secret keys. These six keys are utilized to permute and diffuse the input images. Various security and attack analysis are considered to evaluate the performance of the proposed algorithm. Experimental results reveal that the proposed algorithm can resist various security threats.
Keywords:
Chaotic map
Differential evolution
Bottom-boosting
Secret keys
Six-dimensional hyperchaotic map
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