Cryptography by Synchronization of Hopfield Neural Networks that Simulate Chaotic Signals Generated by the Human Body

被引:2
|
作者
Ramos, Elias de Almeida [1 ]
Britto Filho, Joao Carlos [1 ]
Reis, Ricardo [2 ]
机构
[1] Univ Fed Rio Grande do Sul, PGMICRO, Porto Alegre, RS, Brazil
[2] Univ Fed Rio Grande do Sul, PPGC PGMICRO, Porto Alegre, RS, Brazil
关键词
Cryptography; Dynamical Systems; Synchronization; Neural networks; FPGA;
D O I
10.1109/newcas44328.2019.8961314
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页数:4
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