Return
Secure hash function based on neural network
DOI:10.1016/j.neucom.2006.04.003.png)
Abstract
En 中文
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. (c) 2006 Elsevier B.V. All rights reserved.
Keywords:
neural networks
chaotic neural networks
hash function
digital signature
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
6.5
Papers:
2.5W
Citations:
6.5W
Organization
No organization information available
Cited Papers
Pioneering a golden age of cerebral microcircuits: The births of the combined Golgi–electron microscope methods
Neuroscience
IF0

