Securing grayscale image using improved Arnold transform and ElGamal encryption

Title

Securing grayscale image using improved Arnold transform and ElGamal encryption

Creator

Thomas S.; Krishna A.

Description

The security of sensitive data is critical, and it opens up a wide area of research to find efficient and effective methods to prevent unauthorized access. Our study provides a secure framework for sending visual information over an untrusted channel, such as a social networking site. The proposed framework is a combination of scrambling and encryption techniques. Initially, a hybrid block-wise and pixel-wise scrambling approach is administered to the grayscale image, followed by the Arnold transform, which causes all pixel points to move within the image. Finally, to improve the efficiency of the diffusion process, the asymmetric encryption ElGamal algorithm has been mastered. Peak-signal-To-noise ratio (PSNR), structural similarity index metric (SSIM), number of pixels change rate (NPCR), and unified average changing intensity (UACI) are the metrics utilized to evaluate the efficiency of the proposed scheme. The efficiency of the suggested scheme validates the low-Average PSNR value of <9 dB and the SSIM average value of <0.01 for the encrypted images. The NPCR and UACI values achieved in our study are above the threshold values of 99.6% and 33.33%, respectively, exhibiting the strength of the proposed framework. 2022 SPIE and IS&T.

Source

Journal of Electronic Imaging, Vol-31, No. 6

Date

2022-01-01

Publisher

SPIE

Subject

cryptography; data security; decoding; diffusion; encoding

Coverage

Thomas S., Christ University, School of Engineering and Technology, Department of Computer Science and Engineering, Bangalore, Karnataka, India; Krishna A., Christ University, School of Engineering and Technology, Department of Computer Science and Engineering, Bangalore, Karnataka, India, Rajagiri College of Social Sciences (Autonomous), Department of Computer Science, Cochin, Kerala, India

Rights

Restricted Access

Relation

ISSN: 10179909; CODEN: JEIME

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.1117/1.JEI.31.6.063012

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