Comprehensive Survey on Image Encryption Algorithm for Secure Image Transmission using Chaotic Mapping System
- DOI
- 10.2991/978-94-6239-616-6_98How to use a DOI?
- Keywords
- Chaotic Map; Image Encryption; Secure Image Transmission; Chaos Theory; 3D Henon Map; Lorenz Map
- Abstract
The growing dependency on digital communication and the rapid expansion of image sharing over public networks have made secure image transmission a critical necessity. Chaos theory, characterized by sensitivity to initial conditions, pseudo-random behavior, and non-periodicity, offers unique advantages for encryption by generating unpredictable key streams and highly efficient scrambling. This survey focuses on chaotic map–based image encryption algorithms designed for secure image transmission. We review 15 significant works that employ techniques such as 3D Henon maps, Lorenz maps, Arnold Cat maps, Unified Chaotic Maps, and hyper-chaotic systems. The survey highlights methodologies, security performance metrics (Shannon entropy, NPCR, UACI, correlation coefficients), computational efficiency, and resistance to cryptographic attacks. Challenges such as scalability, robustness against noise, and deployment in cloud or real-time environments are also discussed, along with potential future research directions.
- Copyright
- © 2026 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - R. Anandkumar AU - B. Shanmugapriyan AU - R. J. Arun Roshaan AU - P. Pathytharan PY - 2026 DA - 2026/03/31 TI - Comprehensive Survey on Image Encryption Algorithm for Secure Image Transmission using Chaotic Mapping System BT - Proceedings of the International Conference on Artificial Intelligence and Secure Data Analytics (ICAISDA 2025) PB - Atlantis Press SP - 1336 EP - 1343 SN - 1951-6851 UR - https://doi.org/10.2991/978-94-6239-616-6_98 DO - 10.2991/978-94-6239-616-6_98 ID - Anandkumar2026 ER -