AN ONLINE NEURAL-NETWORK SYSTEM FOR COMPUTER ACCESS SECURITY

被引：25

作者：

OBAIDAT, MS

MACCHIAROLO, DT

机构：

[1] The Department of Electrical Engineering, City College of New York, New York, NY

[2] AT & T Microelectronics Division, Greensboro, Greensboro, NC

来源：

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS | 1993年 / 40卷 / 02期

关键词：

D O I：

10.1109/41.222645

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a new method of identifying computer users based on the individual typing technique of the users. The identification system is a pattern classification system based on a simulation of an artificial neural network. The user types a known sequence of characters, and the intercharacter times represent a pattern vector to be classified. This vector is presented to the classification system, and the pattern is assigned to a predefined class, thus identifying the user. The major work is divided into two phases: the investigation phase and the implementation phase. Experimental results are discussed, followed by a description of a real-time implementation of this system, using a personal computer, known as the On-Line User Identification System. In an operational trial, the system correctly identified users 97.8% of the time. This intelligent system can be used to improve computer security, in addition to the traditional user name and password procedures, in a cost-effective manner.

引用

页码：235 / 242

页数：8

共 16 条

[1]

Bleha S., Obaidat M.S., Dimensionality reduction and feature extraction applications in identifying computer users, IEEE Trans. Sys. Man. Cybem, 21, pp. 452-456, (1991)

[2]

Gorman R., Sejnowski T., Analysis of hidden units in a layered network trained to classify sonar targets, Neural Networks, 1, pp. 75-89, (1988)

[3]

Gullichsen E., Chang E., Pattern classification by neural network: An experimental system for icon recognition, Proc. IEEE 1st Int. Conf Neural Networks, 4, pp. 725-732, (1987)

[4]

Pao Y., Adaptive Pattern Recognition and Neural Networks, (1989)

[5]

Roth M., Survey of neural network technology for automatic target recognition, IEEE Trans. Neural Networks, 1, pp. 28-43, (1990)

[6]

Widrow B., Lehr M., 30 years of adaptive neural networks: Perceptron, Madaline, and backpropagation, Proc. IEEE, 78, pp. 1415-1442, (1990)

[7]

Widrow B., Winter R., Neural nets for adaptive filtering and adaptive pattern recognition, IEEE Computer Mag, pp. 25-39, (1988)

[8]

Tou J.T., Gonzalez R.C., Pattern Recognition Principles, (1974)

[9]

Rumelhart D.E., Hinton G.E., Williams R.J., Learning internal representation by error propagation, Parallel Distributed Processing, (1986)

[10]

Hecht-Nielson R., Neurocomputing, (1990)

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