2007•Unpublished venueRequires access

Strengthening Passwords by Keystroke Dynamics

Attila Meszaros, Zoltán Bankó, László Czúni

Open publisher page 19 citations

Abstract

This document presents the application of biometrics to strength conventional passwords. We show methods to analyze and compare users' keystroke patterns to be able to verify their identity when entering the password into a computer system. The problem's difficulty arises from the fact that only a very limited amount data is available and that new users can come and others may leave the system meantime. That is we are not allowed to re-evaluate all users' data during the application. We show test results based on 2400 records collected from 25 users of different typing ability.

About this research paper

What this paper is about

This document presents the application of biometrics to strength conventional passwords. We show methods to analyze and compare users' keystroke patterns to be able to verify their identity when entering the password into a computer system. The problem's difficulty arises from the fact that only a very limited amount data is available and that new users can come and others may leave the system meantime. That is we are not allowed to re-evaluate all users' data during the application. We show test results based on 2400 records collected from 25 users of different typing ability.

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OpenAlex reports 19 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This document presents the application of biometrics to strength conventional passwords. We show methods to analyze and compare users' keystroke patterns to be able to verify their identity when entering the password into a computer system. The problem's difficulty arises from the fact that only a very limited amount data is available and that new users can come and others may leave the system meantime. That is we are not allowed to re-evaluate all users' data during the application. We show test results based on 2400 records collected from 25 users of different typing ability.

Key concepts: Keystroke dynamics, Password, Keystroke logging, Computer science, Biometrics, Authentication (law), Computer security, Identity (music)

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