Ponente
Descripción
Recent information and communication developments have bust the growth of e-Healthcare as one of the main technology trends of future years, leading to the success of many primary care systems. This progress compel scientist to further improve digital security of sensitive medical information. In this context, chaos-based encryption emerges as one of the most prolific solutions in regards of this issue. Due long term unpredictably of chaotic systems, medical images can be safely secured, but further improvements must be done in order to insure data encryption. Our work develops the analog design of Hopfield neural network with chaotic behavior for a wide range of possible parameters/keys. Moreover, the system’s complex dynamics are applied using an image encryption technique, achieving secure information transmission and meeting essential cryptographic requirements.
