Cellular neural networks in secure transmission applications

Author

Caponetto, R. ; Lavorgna, M. ; Occhipinti, L.

Author_Institution

Soft Comput. & Multimedia Archit. Group, SGS-Thomson Microelectron., Catania, Italy

fYear

1996

Firstpage

411

Lastpage

416

Abstract

The work deals with a state controlled cellular neural network-based circuit for secure transmission applications. Basic principles of synchronisation between two (or more) chaotic systems are reported concerning the inverse system technique. Fundamentals of this kind of transmission are briefly introduced together with some experimental results. Finally, programmability of CNN circuits is exploited in order to increase the transmission security allowing the possibility to set-up several encryption/decryption key codes

Keywords

cellular neural nets; chaos; cryptography; neural chips; chaotic systems; encryption/decryption key codes; inverse system technique; programmability; secure transmission applications; state controlled cellular neural network-based circuit; synchronisation; transmission security; Cellular neural networks; Chaos; Chaotic communication; Circuits; Computer architecture; Computer networks; Intelligent networks; Microelectronics; Multimedia computing; Resistors;

fLanguage

English

Publisher

ieee

Conference_Titel

Cellular Neural Networks and their Applications, 1996. CNNA-96. Proceedings., 1996 Fourth IEEE International Workshop on

Conference_Location

Seville

Print_ISBN

0-7803-3261-X

Type

conf

DOI

10.1109/CNNA.1996.566609

Filename

566609