Keystroke Dynamics in the pre-Touchscreen Era
Biometric authentication seeks to measure an individual’s unique physiological attributes for the purpose of identity verification. Conventionally, this task has been realised via analyses of fingerprints or signature iris patterns. However, whilst such methods effectively offer a superior security...
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Online Access: | http://journal.frontiersin.org/Journal/10.3389/fnhum.2013.00835/full |
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doaj-80c68b6b52c248c589ed5d2c449756032020-11-25T02:03:59ZengFrontiers Media S.A.Frontiers in Human Neuroscience1662-51612013-12-01710.3389/fnhum.2013.0083565063Keystroke Dynamics in the pre-Touchscreen EraNasir eAhmad0Andrea eSzymkowiak1Paul eCampbell2University of DundeeUniversity of Abertay DundeeUniversity of DundeeBiometric authentication seeks to measure an individual’s unique physiological attributes for the purpose of identity verification. Conventionally, this task has been realised via analyses of fingerprints or signature iris patterns. However, whilst such methods effectively offer a superior security protocol compared with password-based approaches for example, their substantial infrastructure costs, and intrusive nature, make them undesirable, and indeed impractical for many scenarios. An alternative approach seeks to develop similarly robust screening protocols through analysis of typing patterns, formally known as keystroke dynamics. Here, keystroke analysis methodologies can utilise multiple variables, and a range of mathematical techniques, in order to extract individuals' typing signatures. Such variables may include measurement of the period between key presses, and/or releases, or even key-strike pressures. Statistical methods, neural networks, and fuzzy logic have often formed the basis for quantitative analysis on the data gathered, typically from conventional computer keyboards. Extension to more recent technologies such as numerical keypads and touch-screen devices is in its infancy, but obviously important as such devices grow in popularity. Here, we review the state of knowledge pertaining to authentication via conventional keyboards with a view towards indicating how this platform of knowledge can be exploited and extended into the newly emergent type-based technological contexts.http://journal.frontiersin.org/Journal/10.3389/fnhum.2013.00835/fullsecurityIdentityauthenticationkeystroke analysispre-touchscreen |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Nasir eAhmad Andrea eSzymkowiak Paul eCampbell |
spellingShingle |
Nasir eAhmad Andrea eSzymkowiak Paul eCampbell Keystroke Dynamics in the pre-Touchscreen Era Frontiers in Human Neuroscience security Identity authentication keystroke analysis pre-touchscreen |
author_facet |
Nasir eAhmad Andrea eSzymkowiak Paul eCampbell |
author_sort |
Nasir eAhmad |
title |
Keystroke Dynamics in the pre-Touchscreen Era |
title_short |
Keystroke Dynamics in the pre-Touchscreen Era |
title_full |
Keystroke Dynamics in the pre-Touchscreen Era |
title_fullStr |
Keystroke Dynamics in the pre-Touchscreen Era |
title_full_unstemmed |
Keystroke Dynamics in the pre-Touchscreen Era |
title_sort |
keystroke dynamics in the pre-touchscreen era |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Human Neuroscience |
issn |
1662-5161 |
publishDate |
2013-12-01 |
description |
Biometric authentication seeks to measure an individual’s unique physiological attributes for the purpose of identity verification. Conventionally, this task has been realised via analyses of fingerprints or signature iris patterns. However, whilst such methods effectively offer a superior security protocol compared with password-based approaches for example, their substantial infrastructure costs, and intrusive nature, make them undesirable, and indeed impractical for many scenarios. An alternative approach seeks to develop similarly robust screening protocols through analysis of typing patterns, formally known as keystroke dynamics. Here, keystroke analysis methodologies can utilise multiple variables, and a range of mathematical techniques, in order to extract individuals' typing signatures. Such variables may include measurement of the period between key presses, and/or releases, or even key-strike pressures. Statistical methods, neural networks, and fuzzy logic have often formed the basis for quantitative analysis on the data gathered, typically from conventional computer keyboards. Extension to more recent technologies such as numerical keypads and touch-screen devices is in its infancy, but obviously important as such devices grow in popularity. Here, we review the state of knowledge pertaining to authentication via conventional keyboards with a view towards indicating how this platform of knowledge can be exploited and extended into the newly emergent type-based technological contexts. |
topic |
security Identity authentication keystroke analysis pre-touchscreen |
url |
http://journal.frontiersin.org/Journal/10.3389/fnhum.2013.00835/full |
work_keys_str_mv |
AT nasireahmad keystrokedynamicsinthepretouchscreenera AT andreaeszymkowiak keystrokedynamicsinthepretouchscreenera AT paulecampbell keystrokedynamicsinthepretouchscreenera |
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