International Journal of Image, Graphics and Signal Processing(IJIGSP)

ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)

Published By: MECS Press

IJIGSP Vol.14, No.4, Aug. 2022

Enhancing Security of Medical Image Data in the Cloud Using Machine Learning Technique

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Chandra Shekhar Tiwari, Vijay Kumar Jha

Index Terms

Arnoldcat mapping, Playfair ciphering, k-means, random forest, image encryption, image decryption, medical image security, security enhancements.


To prevent medical data leakage to third parties, algorithm developers have enhanced and modified existing models and tightened the cloud security through complex processes. This research utilizes PlayFair and K-Means clustering algorithm as double-level encryption/ decryption technique with ArnoldCat maps towards securing the medical images in cloud. K-Means is used for segmenting images into pixels and auto-encoders to remove noise (de-noising); the Random Forest regressor, tree-method based ensemble model is used for classification. The study obtained CT scan-images as datasets from ‘Kaggle’ and classifies the images into ‘Non-Covid’ and ‘Covid’ categories. The software utilized is Jupyter-Notebook, in Python. PSNR with MSE evaluation metrics is done using Python. Through testing-and-training datasets, lower MSE score (‘0’) and higher PSNR score (60%) were obtained, stating that, the developed decryption/ encryption model is a good fit that enhances cloud security to preserve digital medical images.

Cite This Paper

Chandra Shekhar Tiwari, Vijay Kumar Jha, "Enhancing Security of Medical Image Data in the Cloud Using Machine Learning Technique", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.14, No.4, pp. 13-31, 2022. DOI:10.5815/ijigsp.2022.04.02


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