| Title | Cryptography by Synchronization of Hopfield Neural Networks that Simulate Chaotic Signals Generated by the Human Body |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | de Almeida Ramos, Elias, Filho, João Carlos Britto, Reis, Ricardo |
| Conference Name | 2019 17th IEEE International New Circuits and Systems Conference (NEWCAS) |
| Keywords | asymmetric cryptography method, chaotic communication, chaotic cryptography, chaotic signal simulation, chaotic synchronization, composability, cryptography, dynamic systems, Dynamical Systems, encryption circuit, field programmable gate arrays, FPGA, Hopfield neural nets, Hopfield neural networks, human body, Information security, Neural networks, Predictive Metrics, pubcrawl, random number generation, random number sequence, reconfigurable architectures, reconfigurable hardware, Resiliency, synchronisation, Synchronization |
| Abstract | In this work, an asymmetric cryptography method for information security was developed, inspired by the fact that the human body generates chaotic signals, and these signals can be used to create sequences of random numbers. Encryption circuit was implemented in a Reconfigurable Hardware (FPGA). To encode and decode an image, the chaotic synchronization between two dynamic systems, such as Hopfield neural networks (HNNs), was used to simulate chaotic signals. The notion of Homotopy, an argument of topological nature, was used for the synchronization. The results show efficiency when compared to state of the art, in terms of image correlation, histogram analysis and hardware implementation. |
| DOI | 10.1109/NEWCAS44328.2019.8961314 |
| Citation Key | de_almeida_ramos_cryptography_2019 |
Cryptography by Synchronization of Hopfield Neural Networks that Simulate Chaotic Signals Generated by the Human Body