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

摘要：

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 backpropagation is used as the training algorithm.

关键词： Identity Attributes Multimode Authentication Information Fusion Artificial Neural Network

作者: 1Jackson Phiri Tie Jun Zhao

作者单位: Machine Intelligence and Natural Language Processing Group,School of Computer Science, Harbin Institute of Technology,No.11 Siling Street, Nangang District, Harbin, 150001, China

会议类型: 国际会议

会议名称: 2010 International Conference on Communications and Intelligence Information Security(2010年国际信息与智能安全学术会议 ICCIIS2010)

会议地点: 南宁

会议语种:英文

页码: 271-274

在线出版日期: 2010-10-13（万方平台首次上网日期，不代表论文的发表时间）