ArticleSensors (Basel, Switzerland)2021
Medical Images Encryption Based on Adaptive-Robust Multi-Mode Synchronization of Chen Hyper-Chaotic Systems.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 41 citations in OpenAlex.
- A Chaos Synchronization Diagnostic: Difference Time Series Peak Complexity (DTSPC).Entropy (Basel, Switzerland) · 2024Article
- Key dependent information confidentiality scheme based on deoxyribonucleic acid (DNA) and circular shifting.Heliyon · 2024Article
- Medical image encryption algorithm based on a new five-dimensional multi-band multi-wing chaotic system and QR decomposition.Scientific reports · 2024Article
- Medical Image Encryption Based on Josephus Traversing and Hyperchaotic Lorenz System.Journal of Shanghai Jiaotong University (science) · 2022Article
- Time series forecasting of new cases and new deaths rate for COVID-19 using deep learning methods.Results in physics · 2021Article
- Deep neural networks for COVID-19 detection and diagnosis using images and acoustic-based techniques: a recent review.Soft computing · 2021Article
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Authors and funding
8 authors at 7 institutions in 3 countries.
Funding
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Abstract
In this paper, a novel medical image encryption method based on multi-mode synchronization of hyper-chaotic systems is presented. The synchronization of hyper-chaotic systems is of great significance in secure communication tasks such as encryption of images. Multi-mode synchronization is a novel and highly complex issue, especially if there is uncertainty and disturbance. In this work, an adaptive-robust controller is designed for multimode synchronized chaotic systems with variable and unknown parameters, despite the bounded disturbance and uncertainty with a known function in two modes. In the first case, it is a main system with some response systems, and in the second case, it is a circular synchronization. Using theorems it is proved that the two synchronization methods are equivalent. Our results show that, we are able to obtain the convergence of synchronization error and parameter estimation error to zero using Lyapunov's method. The new laws to update time-varying parameters, estimating disturbance and uncertainty bounds are proposed such that stability of system is guaranteed. To assess the performance of the proposed synchronization method, various statistical analyzes were carried out on the encrypted medical images and standard benchmark images. The results show effective performance of the proposed synchronization technique in the medical images encryption for telemedicine application.
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