Secure Image Encryption with Optimized Chaotic Sequences and Multi-layer Cryptographic Operations
Security protection for digital images remains a fundamental issue in contemporary communication systems because it enables secure medical imaging, remote sensing operations, and secure transmission of multimedia content. This research develops an enhanced image encryption method that employs optimi...
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| Vydáno v: | SN computer science Ročník 6; číslo 7; s. 879 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Singapore
Springer Nature Singapore
07.10.2025
Springer Nature B.V |
| Témata: | |
| ISSN: | 2661-8907, 2662-995X, 2661-8907 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Security protection for digital images remains a fundamental issue in contemporary communication systems because it enables secure medical imaging, remote sensing operations, and secure transmission of multimedia content. This research develops an enhanced image encryption method that employs optimised hybrid chaotic mappings, adaptive permutation, and complex substitution layer procedures. The methodology surpasses ordinary encryption methods using one-dimensional maps because it utilizes various chaotic sequences to improve randomness, initial condition sensitivity, and control parameter responsiveness. Pixel permutation occurs through an adaptive key generation process, leading to a multi-stage encryption operation performed through XOR diffusion with modular transformations. Many experimental tests prove that the proposed method provides a solid defence against statistical and differential attacks. Compared to modern image encryption methods, the developed technique achieved better results in correlation reduction, entropy, Number of Pixels Change Rate (NPCR), and Unified Average Changing Intensity (UACI). This framework establishes scalability with optimal functionality for low-resource usage in security systems linked to IoT networks. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 2661-8907 2662-995X 2661-8907 |
| DOI: | 10.1007/s42979-025-04407-1 |