CHNN nonlinear combination generator

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

2 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)257-260
Journal / PublicationProceedings of the IEEE International Conference on Electronics, Circuits, and Systems
Volume2
Publication statusPublished - 1998

Conference

Title1998 5th IEEE International Conference on Electronics, Circuits and Systems (ICECS'98)
LocationInstituto Superior Técnico
PlacePortugal
CityLisboa
Period7 - 10 September 1998

Abstract

We resent a new construction of a combination generator based on a clipped version of Hopfield neural network and maximum-length linear feedback shift registers (LFSRs). The clipped Hopfield neural network (CHNN) acts as a nonlinear combining function on the outputs of the LFSRs, which destroys the linearity and algebraic structure of the LFSRs. The resulting sequences have long period, large linear complexity and key space. The construction is suitable for practical implementation of efficient stream cipher cryptosystems.