Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
411011 | Neurocomputing | 2006 | 5 Pages |
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Shiguo Lian, Jinsheng Sun, Zhiquan Wang,