Enhancing image security through nonlinear preprocessing and double random phase encoding using fractional fourier transform.

Saved in:

Bibliographic Details
Title:	Enhancing image security through nonlinear preprocessing and double random phase encoding using fractional fourier transform.
Authors:	Radjah, Fayçal¹ radjah.faycal@yahoo.fr, Diffellah, Nacira² nacira.diffellah@univ-bba.dz, Bekkouche, Tewfik³ toufik.bekkouche@univ-bba.dz, Ziet, Lahcene¹ lahcene.ziet@univ-setif.dz
Source:	Telkomnika. Jun2026, Vol. 24 Issue 3, p1003-1013. 11p.
Subjects:	Image encryption, Image processing, Cryptography, Signal-to-noise ratio, Data transmission system security measures
Abstract:	Image encryption is crucial for secure data transmission in fields such as IoT, medical imaging, and biometrics. This paper proposes an enhanced encryption framework that combines nonlinear preprocessing with double random phase encoding (DRPE) using the fractional fourier transform (FrFT). The diffusion process replaces the conventional XOR operation with a nonlinear hyperbolic tangent (tanh) function, improving confusion diffusion complexity and resistance to cryptanalytic attacks. Experimental results show a reduction in peak signal-to-noise ratio (PSNR) from 9.03 dB to 7.25 dB and a mean squared error (MSE) increase to 10×10³, indicating stronger encryption and lower correlation with the original image. The proposed method also enhances robustness against histogram and keysensitivity attacks. Statistical analyses, including entropy and number of pixels change rate (NPCR) metrics, demonstrate that the approach outperforms conventional DRPE methods while maintaining computational efficiency. This hybrid nonlinear and FrFT-based framework provides a practical and scalable solution for secure image transmission in sensitive and real-time applications. [ABSTRACT FROM AUTHOR]
	Copyright of Telkomnika is the property of Department of Electrical Engineering, Ahmad Dahlan University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database:	Engineering Source

Description
Abstract:	Image encryption is crucial for secure data transmission in fields such as IoT, medical imaging, and biometrics. This paper proposes an enhanced encryption framework that combines nonlinear preprocessing with double random phase encoding (DRPE) using the fractional fourier transform (FrFT). The diffusion process replaces the conventional XOR operation with a nonlinear hyperbolic tangent (tanh) function, improving confusion diffusion complexity and resistance to cryptanalytic attacks. Experimental results show a reduction in peak signal-to-noise ratio (PSNR) from 9.03 dB to 7.25 dB and a mean squared error (MSE) increase to 10×10³, indicating stronger encryption and lower correlation with the original image. The proposed method also enhances robustness against histogram and keysensitivity attacks. Statistical analyses, including entropy and number of pixels change rate (NPCR) metrics, demonstrate that the approach outperforms conventional DRPE methods while maintaining computational efficiency. This hybrid nonlinear and FrFT-based framework provides a practical and scalable solution for secure image transmission in sensitive and real-time applications. [ABSTRACT FROM AUTHOR]
ISSN:	16936930
DOI:	10.12928/TELKOMNIKA.v24i3.27650