One-way Hash Function Based on Neural Network
Cryptography and Security
2007-07-30 v1 Neural and Evolutionary Computing
Abstract
A hash function is constructed based on a three-layer neural network. The three neuron-layers are used to realize data confusion, diffusion and compression respectively, and the multi-block hash mode is presented to support the plaintext with variable length. Theoretical analysis and experimental results show that this hash function is one-way, with high key sensitivity and plaintext sensitivity, and secure against birthday attacks or meet-in-the-middle attacks. Additionally, the neural network's property makes it practical to realize in a parallel way. These properties make it a suitable choice for data signature or authentication.
Keywords
Cite
@article{arxiv.0707.4032,
title = {One-way Hash Function Based on Neural Network},
author = {Shiguo Lian and Jinsheng Sun and Zhiquan Wang},
journal= {arXiv preprint arXiv:0707.4032},
year = {2007}
}
Comments
7 pages,5 figures,submitted