### Abstract

The chaos synchronization system used for secrecy communication is considered. The compound system which consists of subsystems is chaos-synchronized. In order to increase the secrecy of models of subsystem, state of synchronization section in each subsystem is constituted by fuzzy model. Subsystems with the same chaotic dynamics are asynchronous at first. The considered non-linear feedback control is applied to the chaos synchronization control. The control input for the chaos synchronization can be made small by use of the Unstable Periodic Regions based on the chaotic characteristic of the subsystems, then. It is important that the mathematical model of the chaos system used in synchronization sections or the encryption section is not known by the third person. However, the mathematical model of the chaos known well is used for them. Using the state of the chaos synchronization section, bifurcation parameter is changed and chaos modulations are performed. And the chaos state of the encryption section is used for encryption of information signals. The chaos dynamics of the encryption section is generated using Chaos Neuron dynamics of Chaos Neural Network.

Original language | English |
---|---|

Pages (from-to) | 97-108 |

Number of pages | 12 |

Journal | International Journal of Innovative Computing, Information and Control |

Volume | 5 |

Issue number | 1 |

Publication status | Published - 2009 Jan |

### Fingerprint

### Keywords

- Chaos synchronization
- Fuzzy model
- Secrecy communication

### ASJC Scopus subject areas

- Computational Theory and Mathematics
- Information Systems
- Software
- Theoretical Computer Science

### Cite this

*International Journal of Innovative Computing, Information and Control*,

*5*(1), 97-108.

**A method of the secrecy communication using fuzzy and chaos.** / Shimizu, Yoshimasa; Miyazaki, Michio; Qian, Fei; Lee, HeeHyol.

Research output: Contribution to journal › Article

*International Journal of Innovative Computing, Information and Control*, vol. 5, no. 1, pp. 97-108.

}

TY - JOUR

T1 - A method of the secrecy communication using fuzzy and chaos

AU - Shimizu, Yoshimasa

AU - Miyazaki, Michio

AU - Qian, Fei

AU - Lee, HeeHyol

PY - 2009/1

Y1 - 2009/1

N2 - The chaos synchronization system used for secrecy communication is considered. The compound system which consists of subsystems is chaos-synchronized. In order to increase the secrecy of models of subsystem, state of synchronization section in each subsystem is constituted by fuzzy model. Subsystems with the same chaotic dynamics are asynchronous at first. The considered non-linear feedback control is applied to the chaos synchronization control. The control input for the chaos synchronization can be made small by use of the Unstable Periodic Regions based on the chaotic characteristic of the subsystems, then. It is important that the mathematical model of the chaos system used in synchronization sections or the encryption section is not known by the third person. However, the mathematical model of the chaos known well is used for them. Using the state of the chaos synchronization section, bifurcation parameter is changed and chaos modulations are performed. And the chaos state of the encryption section is used for encryption of information signals. The chaos dynamics of the encryption section is generated using Chaos Neuron dynamics of Chaos Neural Network.

AB - The chaos synchronization system used for secrecy communication is considered. The compound system which consists of subsystems is chaos-synchronized. In order to increase the secrecy of models of subsystem, state of synchronization section in each subsystem is constituted by fuzzy model. Subsystems with the same chaotic dynamics are asynchronous at first. The considered non-linear feedback control is applied to the chaos synchronization control. The control input for the chaos synchronization can be made small by use of the Unstable Periodic Regions based on the chaotic characteristic of the subsystems, then. It is important that the mathematical model of the chaos system used in synchronization sections or the encryption section is not known by the third person. However, the mathematical model of the chaos known well is used for them. Using the state of the chaos synchronization section, bifurcation parameter is changed and chaos modulations are performed. And the chaos state of the encryption section is used for encryption of information signals. The chaos dynamics of the encryption section is generated using Chaos Neuron dynamics of Chaos Neural Network.

KW - Chaos synchronization

KW - Fuzzy model

KW - Secrecy communication

UR - http://www.scopus.com/inward/record.url?scp=64349103243&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=64349103243&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:64349103243

VL - 5

SP - 97

EP - 108

JO - International Journal of Innovative Computing, Information and Control

JF - International Journal of Innovative Computing, Information and Control

SN - 1349-4198

IS - 1

ER -