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A hybrid crypto-compression model for secure brain mri image transmission

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Abstract

Medical image encryption is a major issue in healthcare applications where memory, energy, and computational resources are constrained. The modern technological architecture of digital healthcare systems is, in fact, insufficient to handle both the current and future requirements for data. Security has been raised to the highest priority. By meeting these conditions, the hybrid crypto-compression technique introduced in this study can be used for securing the transfer of healthcare images. The approach consists of two components. In order to construct a cutting-edge generative lossy compression system, we first combine generative adversarial networks (GANs) with oearned compression. As a result, the second phase might address this problem by using highly effective picture cryptography techniques. A randomly generated public key is subjected to the DNA technique. In this application, pseudo-random bits are produced by using a logistic chaotic map algorithm. During the substitution process, an additional layer of security is provided to boost the technique’s fault resilience. Our proposed system and security investigations show that the method provides trustworthy and long-lasting encryption and several multidimensional aspects that have been discovered in various public health and healthcare issues. As a result, the recommended hybrid crypto-compression technique may significantly reduce a photo’s size and remain safe enough to be used for medical image encryption.

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Authors declare that all the data being used in the design and production cum layout of the manuscript is declared in the manuscript.

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Funding

The authors received no specific funding for this study.

Author information

Authors and Affiliations

  1. School of Computing Science and Engineering, VIT Bhopal University, Bhopal-Indore Highway, Kothrikalan, 466114, Sehore Madhya Pradesh, India

    Sasmita Padhy

  2. Department of Computer Science and Engineering, GIET University, Gunupur, Odisha, India

    Sachikanta Dash

  3. Department of Computer Engineering and Technology, Dr. Vishwanath Karad MIT World Peace University, Pune, Maharashtra, India

    T. N. Shankar

  4. Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, India

    Venubabu Rachapudi

  5. Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, 560074, Karnataka, India

    Sandeep Kumar

  6. Graduate School, Duy Tan University, Da Nang, Vietnam

    Anand Nayyar

  7. Faculty of Information Technology, Duy Tan University, Da Nang, Vietnam

    Anand Nayyar

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  1. Sasmita Padhy
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  2. Sachikanta Dash
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  4. Venubabu Rachapudi
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  5. Sandeep Kumar
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Correspondence to Anand Nayyar.

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Padhy, S., Dash, S., Shankar, T.N. et al. A hybrid crypto-compression model for secure brain mri image transmission. Multimed Tools Appl 83, 24361–24381 (2024). https://doi.org/10.1007/s11042-023-16359-w

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