Using Shannon´s Information Theory and Artificial Neural Networks to Implement Multimode Authentication

Author

Phiri, Jackson ; Tie Jun Zhao

Author_Institution

Machine Intell. & Natural Language Process. Group, Harbin Inst. of Technol., Harbin, China

fYear

2010

fDate

13-14 Oct. 2010

Firstpage

271

Lastpage

274

Abstract

Artificial intelligence technologies have been applied in a number of systems to achieve learning and intelligent behavior. In this paper an artificial neural network is used to implement multimode authentication through information fusion. An information fusion model uses metrics computed from the identity attributes using Shannon´s information theory. Initialisation of the artificial neural network is achieved by using the Nguyen-Widrow function while Levenberg-Marquardt back propagation is used as the training algorithm.

Keywords

information theory; learning (artificial intelligence); message authentication; neural nets; Levenberg-Marquardt back propagation; Nguyen-Widrow function; Shannon´s information theory; artificial intelligence technologies; artificial neural networks; identity attributes; information fusion model; intelligent behavior; learning behavior; metrics computed; multimode authentication; training algorithm; Artificial neural networks; Authentication; Hidden Markov models; Information theory; Measurement; Neurons; Training; Artificial Neural Network; Identity Attributes; Information Fusion; Multimode Authentication;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications and Intelligence Information Security (ICCIIS), 2010 International Conference on

Conference_Location

Nanning

Print_ISBN

978-1-4244-8649-6

Electronic_ISBN

978-0-7695-4260-7

Type

conf

DOI

10.1109/ICCIIS.2010.38

Filename

5629239