Open Access

ARTICLE

Efficient Medical Image Encryption Framework against Occlusion Attack

May A. Al-Otaibi^1,*, Hesham Alhumyani¹, Saleh Ibrahim², Alaa M. Abbas²

1 Department of Computer Engineering, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
2 Department of Electrical Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia

* Corresponding Author: May A. Al-Otaibi. Email:

Intelligent Automation & Soft Computing 2022, 34(3), 1523-1536. https://doi.org/10.32604/iasc.2022.026161

Received 16 December 2021; Accepted 05 February 2022; Issue published 25 May 2022

Abstract

Image encryption has attracted a lot of interest as an important security application for protecting confidential image data against unauthorized access. An adversary with the power to manipulate cipher image data can crop part of the image out to prevent decryption or render the decrypted image useless. This is known as the occlusion attack. In this paper, we address a vulnerability to the occlusion attack identified in the medical image encryption framework recently proposed in []. We propose adding a pixel scrambling phase to the framework and show through simulation that the extended framework effectively mitigates the occlusion attack while maintaining the other attractive security features. The scrambling is performed using a separate chaotic map which is securely initialized using a secret key and a random nonce to deter chosen-plaintext attacks. Moreover, we show through simulation that the choice of chaotic map used for scrambling is irrelevant to the effectiveness of the scrambling algorithm against the occlusion attack.

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Keywords

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