Hash Function Construction Based on RBFNN and Chaotic Mapping

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Author(s)

Jun Chen 1,* Chunxiao He 2 Pengcheng Wei 3

1. Dean’s Office Chongqing Education College Chongqing 400067, China

2. Teaching and Research Section of Computer Chongqing Education Management School Chongqing 400066, China

3. Department of Computer Science Chongqing Education College Chongqing 400067, China

* Corresponding author.

DOI: https://doi.org/10.5815/ijem.2011.04.01

Received: 5 May 2011 / Revised: 16 Jun. 2011 / Accepted: 21 Jul. 2011 / Published: 29 Aug. 2011

Index Terms

RBF neural network, Chaotic mapping, Hash function

Abstract

One-way Hash function is not only widely used in the aspects of the digital signature, identity authentication and integrity checking, etc. but also the research hotspot in the field of contemporary cryptography. In this paper, it firstly utilized neural network and practiced the chaotic sequences produced by one-dimensional nonlinear mapping. And then, it constructed Hash function with cipherkey by means of altering sequences. One of the advantages of this algorithm is that neural network hides the chaotic mapping relations and make it difficult to obtain mapping directly. Simulation experiment showed that the algorithm have good unidirectionality and weak collision, and stronger confidentiality than the tradition-based Hash function, as well as easy to achieve.

Cite This Paper

Jun Chen,Chunxiao He,Pengcheng Wei,"Hash Function Construction Based on RBFNN and Chaotic Mapping", IJEM, vol.1, no.4, pp.1-9, 2011. DOI: 10.5815/ijem.2011.04.01 

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