An Improved Scheme for Neural Synchronization Based on Tree Parity Machine

doi:10.3969/j.issn.1006-2475.2014.05.011

Abstract

Abstract: Neural network can fully synchronize by learning from each other, because this effect neural synchronization can be used to construct a cryptographic key-exchange protocol, which has become an important research direction in current cryptography. To solve the problem of too many times in neural cryptography synchronization, an improved scheme was proposed by employing Tree Parity Machine (TPM). On the basis of neural cryptographic protocols, the range of initial weights of neural units was appropriately reduced. After the analysis, the simulation results show that in the case of ensuring security, synchronization efficiency is greatly improved by applying new improvement scheme.
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Key words: tree parity machine, neural synchronization, key-exchange, neural cryptography
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CLC Number:

TP309.7

LIU Yi-lu, LIAO Xiao-feng, LIANG Yi-feng. An Improved Scheme for Neural Synchronization Based on Tree Parity Machine[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2014.05.011.

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