Vol. 1 No. 1 (2023): Jan/June - Issue - 01
Articles

A Modified Framework for Image Encryption and Decryption Using Modified Chaotic Algorithms Towards Medical Image Security

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  • Nagashree N,
  • Shantakumar Patil,
  • Narayan K,
  • Chethana N,
  • Chandana N,
  • Rakshitha Mansi H T,
  • Sparshithraj
Nagashree N
Department of Computer Science and Engineering Sai Vidya Institute of Technology, VTU, Bangalore, Karnataka, India.
Shantakumar Patil
Department of Computer Science and Engineering, Sai Vidya Institute of Technology, VTU, Bangalore, Karnataka, India.
Narayan K
NITTE Meenakshi Institute of Technology, VTU, Bangalore, Karnataka, India.
Chethana N
Department of Computer Science and Engineering, Sai Vidya Institute of Technology, VTU, Bangalore, Karnataka, India.
Chandana N
Department of Computer Science and Engineering, Sai Vidya Institute of Technology, VTU, Bangalore, Karnataka, India.
Rakshitha Mansi H T
Department of Computer Science and Engineering, Sai Vidya Institute of Technology, VTU, Bangalore, Karnataka, India.
Sparshithraj
Department of Computer Science and Engineering, Sai Vidya Institute of Technology, VTU, Bangalore, Karnataka, India.
DOI: https://doi.org/10.5281/zenodo.8069902

Published 2023-06-23

Keywords

  • Arnold mapping,
  • Henon, Harris,
  • Image encryption,
  • modified chaotic algorithm

How to Cite

Nagashree N, Shantakumar Patil, Narayan K, Chethana N, Chandana N, Rakshitha Mansi H T, & Sparshithraj. (2023). A Modified Framework for Image Encryption and Decryption Using Modified Chaotic Algorithms Towards Medical Image Security. Milestone Transactions on Medical Technometrics, 1(1), 1–9. https://doi.org/10.5281/zenodo.8069902

Abstract

The brain child of the paper is to design a framework for performing secure medical image transmission via networks. There are several image cryptographic techniques available for better encryption and decryption of images. This paper proposes a modified chaotic algorithm based on Arnold cat map and Hanon map using Harris corner detector to secure the images at extra level. The proposed framework has given around 98% of accuracy in contrast to the earlier existing methods. The performance evaluators are executed to measure the accuracy of proposed system.

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References

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