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Blockchain based medical image encryption using Arnold's cat map in a cloud environment.

Saba Inam1, Shamsa Kanwal2, Rabia Firdous2

  • 1Department of Mathematical Sciences, Fatima Jinnah Women University, The Mall, Rawalpindi, Pakistan. saba.inam@fjwu.edu.pk.

Scientific Reports
|March 7, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a novel Blockchain-based Chaotic Arnold's cat map Encryption Scheme (BCAES) for secure medical image processing. The BCAES enhances data security in cloud environments by encrypting images and storing their signatures on a blockchain, ensuring integrity and authenticity.

Keywords:
Arnold’s cat mapBlockchainCloud computingOrthogonal matrixStructural similarity index measure (SSIM)

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Area of Science:

  • Medical Imaging and Data Security
  • Cloud Computing and Blockchain Technology
  • Cryptography and Information Assurance

Background:

  • Modern healthcare generates vast amounts of sensitive data, posing significant security challenges for storage and transmission.
  • Public cloud storage for medical data risks eavesdropping, data breaches, and unauthorized access.
  • Existing security measures require enhancement to ensure the integrity and confidentiality of digital health records.

Purpose of the Study:

  • To propose a novel encryption scheme integrating blockchain and chaotic map encryption for secure medical image transactions.
  • To address the security vulnerabilities associated with storing and transmitting medical data in cloud environments.
  • To ensure data integrity and authenticity for medical image data receivers.

Main Methods:

  • Implementation of a Blockchain-based Chaotic Arnold's cat map Encryption Scheme (BCAES).
  • Encryption of medical images using Arnold's cat map algorithm before cloud transmission.
  • Storing signed documents of plain images on a blockchain for verification.
  • Utilizing blockchain's distributed nature and consensus mechanisms for enhanced security.

Main Results:

  • The BCAES scheme demonstrated high efficiency in various analytical tests including key sensitivity, key space, information entropy, and correlation.
  • Performance metrics such as PSNR, NPCR, UACI, MSE, and SSIM indicate robust encryption capabilities.
  • The proposed scheme shows superior performance compared to recent encryption methods in the literature.

Conclusions:

  • The BCAES offers a secure and efficient solution for medical image processing and data management in cloud environments.
  • The integration of blockchain technology significantly enhances the trustworthiness and security of medical data transactions.
  • This approach sets a new benchmark for securing sensitive medical information against unauthorized access and breaches.