Hyperchaos and the fusion of Moore’s automaton with gold sequences for augmented medical image encryption
Year: 2025
Type: article
Abstract: This study presents a sophisticated encryption methodology specifically designed for the secure transfer of medical images across cloud services. The initial phase of the algorithm involves the consolidation of multiple images to form a single augmented image, which is then subjected to the first layer of encryption. This layer employs an encryption key and an S-box generated through a Memristive Coupled Neural Network Model (MCNNM), establishing a strong foundation for security. Following this, the novel integration of Moore's Automaton with Gold sequences is applied as a confusion mechanism, intrinsically scrambling the image structure to effectively disrupt pixel correlations. The encryption process iterates over N cycles, significantly deepening the level of encryption with each iteration. Performance evaluations reflect a considerable key space of [Formula: see text] and a high encryption rate of 15.5 Mbps, while rigorous statistical tests validate the algorithm's resilience. The encryption system proposed in this manuscript not only ensures a formidable level of security but is also pragmatically designed for application in the protection of sensitive healthcare data.
Source: Scientific Reports
Institutions: German University in Cairo, Cairo University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,690
Funder: German University in Cairo
OpenAlex ID: W4417279097