Performance of keystroke biometrics authentication system using Multilayer Perceptron neural network (MLP NN)

N. Harun*, S. S. Dlay, W. L. Woo

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

The use of computer has increased rapidly as well as the use of internet applications such as e-commerce, online banking services, webmail, and blogs. All internet applications require a password authentication scheme to make sure only the genuine individual can login to the application. Passwords and personal identification numbers (PIN) have traditionally been used to access such applications. However, it is easy for unauthorized persons to access these systems without detection. This paper addresses the issue of enhancing such systems using keystroke biometrics as a translucent level of user authentication. The paper focuses on using the time interval (key down-down) between keystrokes as a feature of individuals' typing patterns to recognize authentic users and reject imposters. A Multilayer Perceptron (MLP) neural network with a Back Propagation (BP) learning algorithm is used to train and validate the features.

Original languageEnglish
Title of host publication2010 7th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2010
PublisherIEEE
Pages711-714
Number of pages4
ISBN (Electronic)9781861353696
ISBN (Print)9781424488582
Publication statusPublished - 20 Sep 2010
Event2010 7th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2010 - Newcastle upon Tyne, United Kingdom
Duration: 21 Jul 201023 Jul 2010

Conference

Conference2010 7th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2010
CountryUnited Kingdom
CityNewcastle upon Tyne
Period21/07/1023/07/10

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