Abstract
With the advancements in Internet technologies, a huge amount of images are transferred over the public networks. Therefore, during the transmission process, the images are prone to various security threats. To protect images against any unauthorized access, many researchers have designed various approaches such as encryption, stenography, and visual cryptography. Each approach has its own benefits over the others. The main objective of this paper is to design an efficient image encryption approach. Initially, various image encryption approaches have been studied. It is found that the majority of the existing image encryption approaches suffer from the hyperparameters tuning problem. Also, it is desirable to develop secret keys which are highly sensitive to plain images. Therefore, in this paper, an improved seven-dimensional hyperchaotic system (i7DHS) is adopted to generate secret keys. But, i7DHS is sensitive to its initial parameters. Therefore, a dual local search-based evolutionary algorithm (DEA) is utilized to tune the initial parameters of i7DHS. The computed optimal keys are utilized to encrypt the input images. Performance analysis shows that DEA-based i7DHS outperforms the competitive approaches. DEA-based i7DHS is highly sensitive to the input images and has large secret key space. It is found that DEA-based i7DHS can resist various security attacks.





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Kaur, M., Singh, D. & Kumar, V. Improved seven-dimensional (i7D) hyperchaotic map-based image encryption technique. Soft Comput 26, 3703–3712 (2022). https://doi.org/10.1007/s00500-022-06841-2
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DOI: https://doi.org/10.1007/s00500-022-06841-2