A practical approach to user authentication

Author

Brown, Marcus ; Rogers, Samuel J.

Author_Institution

Dept. of Comput. Sci., Alabama Univ., AL, USA

fYear

1994

fDate

5-9 Dec 1994

Firstpage

108

Lastpage

116

Abstract

A method for user authentication is presented which analyzes keystroking data as the user types his or her name. This study utilizes the ADALINE (ADAptive LINear Element) and backpropagation neural nets to identify the typing pattern characteristic of a particular user. A simple measure of geometric distance is also used for comparison. This paper provides a brief introduction to this type of neural net. It then describes the research procedure and contrasts the initial and new results, followed by a conclusion with notes concerning future research. For an average 15-character name, a complete exclusion of imposters is obtained from a set of over 5000 imposter samples

Keywords

authorisation; biometrics (access control); 15-character name; ADALINE neural net; adaptive linear element; backpropagation neural net; geometric distance; imposter exclusion; keystroke analysis; keystroking data; typing pattern characteristic; user authentication; Authentication; Computer science; Computer security; Data analysis; Intellectual property; Neural networks; Pattern analysis; Testing; Timing;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Security Applications Conference, 1994. Proceedings., 10th Annual

Conference_Location

Orlando, FL

Print_ISBN

0-8186-6795-8

Type

conf

DOI

10.1109/CSAC.1994.367316

Filename

367316