Title: Image encryption using deep learning: application of AI in medical images

Authors: Ravi Kishore Veluri; Sulakshana B. Mane; V. Sureka; K. Gokulkannan

Addresses: Computer Science Department, Aditya Engineering College, Surampalem, India ' Computer Engineering, Bharati Vidyapeeth College of Engineering, Navi Mumbai, India ' Department of Computer Science and Engineering, S.A. Engineering College, Chennai, India ' Electronics and Communication Engineering, Saveetha Engineering College, Thandalam, Chennai 602105, India

Abstract: The Fourier frequency domain provides the opportunity to differentiate between the dominant frequency of each collection of pictures. After each group is stacked on top of the others, the ciphertext is scrambled. This process is repeated until the final ciphertext is constructed. Throughout the whole decryption process, deep learning is used in order to improve the speed at which the decryption process is carried out and the quality of the recovered image. In particular, the ciphertext that has been retrieved may be sent into the neural network that has been trained, and after that, the plaintext image can be immediately recreated. The results of experimental study indicate that the CC of the decrypted output may be more than 0.99 when 32 photos are encrypted by the process.

Keywords: optical information security; deep learning; sinusoidal coding; frequency multiplexing.

DOI: 10.1504/IJESDF.2026.152236

International Journal of Electronic Security and Digital Forensics, 2026 Vol.18 No.2, pp.157 - 170

Received: 19 Jan 2024
Accepted: 09 Apr 2024
Published online: 12 Mar 2026 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article