Hash Function Construction Based on RBFNN and Chaotic Mapping
Автор: Jun Chen, Chunxiao He, Pengcheng Wei
Журнал: International Journal of Engineering and Manufacturing(IJEM) @ijem
Статья в выпуске: 4 vol.1, 2011 года.
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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.
RBF neural network, Chaotic mapping, Hash function
Короткий адрес: https://sciup.org/15014140
IDR: 15014140
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