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Secure Image Encryption Model for Cloud-Based Healthcare Storage Using Hyperchaos and DNA Encoding

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Computational Intelligence in Data Science (ICCIDS 2023)

Abstract

In recent years, security and privacy have drawn a lot of attention due to digital communications and the widespread usage of multimedia transmissions over unsecured channels. In every area of analytics, digital images are essential. Sensitive image information like fingerprints, medical records, or defense satellite images needs to be securely stored and processed in a cloud server. In this article, we come up with a novel image encryption model for medical images utilizing a combination of chaotic maps over the DNA-encoded image with bit plane scrambling. Hyperchaotic maps are used to generate confusion keys and Chaotic maps are used for diffusion keys generation. The robustness and resistance of the system to attacks like differential attacks and statistical attacks are shown and extensively analyzed in terms of the security of the proposed model.

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Correspondence to Arun Amaithi Rajan .

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Amaithi Rajan, A., Vetrian, V., Gladys, A. (2023). Secure Image Encryption Model for Cloud-Based Healthcare Storage Using Hyperchaos and DNA Encoding. In: Chandran K R, S., N, S., A, B., Hamead H, S. (eds) Computational Intelligence in Data Science. ICCIDS 2023. IFIP Advances in Information and Communication Technology, vol 673. Springer, Cham. https://doi.org/10.1007/978-3-031-38296-3_8

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  • DOI: https://doi.org/10.1007/978-3-031-38296-3_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-38295-6

  • Online ISBN: 978-3-031-38296-3

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