Manas Kumar Sanyal

Work place: University of Kalyani, West Bengal, India

E-mail: manas_sanyal@rediffmail.com

Website:

Research Interests: Business Intelligence, Machine Learning, Cloud Computing, Deep Learning

Biography

Manas K. Sanyal is a Professor in the Department of Business Administration, University of Kalyani, India. He received his M. Tech degree and Ph.D. in Information Technology. Professor Sanyal has published several research papers in international journals of repute and co-authored a number of books. His interest includes Big Data, Machine Learning, Deep Learning, Business Intelligence and Cloud Computing.

Author Articles
A Hyper-chaotic Medical Image Encryption with Optimized Key Value

By Subhajit Das Manas Kumar Sanyal

DOI: https://doi.org/10.5815/ijisa.2024.03.02, Pub. Date: 8 Jun. 2024

This article delves into a medical image encryption/decryption method based on hyper chaotic dynamics and genetic algorithms. The proposed algorithm boasts simplicity in implementation, featuring straightforward operations that render it well-suited for real-time applications while elevating its security measures. Leveraging the sensitivity of chaotic behavior to initial conditions, a genetic algorithm is employed to select optimal initial conditions for the 5D multi-wing hyper-chaotic system. Initially, a secret key generation method based on the input image is applied, followed by stages of diffusion and encryption utilizing the chaotic system. The secret key undergoes optimization through a genetic algorithm, considering specific parameters within the encrypted image as encryption factors. Subsequently, the encrypted image with the optimized secret key is finalized, serving as the basis for decrypting the cipher image. The proposed method undergoes simulation, testing, and comparison against other image encryption algorithms. Both experimental results and computer simulations affirm the robustness of this cryptographic system, showcasing a significant key space value (2^256), high key sensitivity (Number of Pixels Change Rate: NPCR > 99.55%, Unified Average Changing Intensity: UACI > 33.37%), and its ability to fend off various types of attack.

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