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RISE: Rubik’s cube and image segmentation based secure medical images encryption

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Abstract

Despite the ease of digital image distribution, storage, and replication, averting identity theft, privacy breaches, and ownership issues can be challenging. Medical image encryption plays a vital role in ensuring the confidentiality of sensitive medical data and safeguarding patient privacy. This research addresses these concerns by introducing a novel approach, RISE, to medical image security by using the fusion of chaotic keys and a secret-sharing technique. The key advancement is the use of a Rubik’s cube-based bit-plane shuffling technique to reduce the complexity of strong image encryption, adding a unique dimension to the field of medical image security. Another distinguishing aspect of our approach is the strategic use of segmentation to encrypt only the sensitive part of the image and reduce the time complexity. This area is encrypted using a chaotic key with a Rubik’s cube-based bit-plane shuffling algorithm, followed by the implementation of the confusion process. The encrypted image is shared using a K-N Secret sharing method, which provides authentication and high robustness. The final decrypted image is enhanced using super-resolution to provide better information outputs. The proposed technique offers excellent security and produces better outcomes while being simple. The average NPCR and UACI scores of the proposed encryption technique are 99.47, and 49.90, respectively, and the entropy is 7.995, underscoring the robustness and effectiveness of our proposed approach. It has a high key bit sensitivity and average time complexity. The result analysis further ensures resistance against crop attacks or data loss, positioning it as a formidable contender in the landscape of modern image security.

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Data Availability

The dataset generated during and/or analyzed during the current study are available online [36].

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab, India

    Kunal Demla & Ashima Anand

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  1. Kunal Demla
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  2. Ashima Anand
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Correspondence to Ashima Anand.

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Demla, K., Anand, A. RISE: Rubik’s cube and image segmentation based secure medical images encryption. Multimed Tools Appl (2024). https://doi.org/10.1007/s11042-024-18351-4

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  • DOI: https://doi.org/10.1007/s11042-024-18351-4

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