Keystroke dynamics in password authentication enhancement

Pin Shen Teh; Connie Tee; Thian Song Ong; Andrew Beng Jin Teoh

doi:10.1016/j.eswa.2010.06.097

Keystroke dynamics in password authentication enhancement

Pin Shen Teh, Connie Tee, Thian Song Ong, Andrew Beng Jin Teoh

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Article › peer-review

39 Citations (Scopus)

Abstract

This paper describes a novel technique to strengthen password authentication system by incorporating multiple keystroke dynamic information under a fusion framework. We capitalize four types of latency as keystroke feature and two methods to calculate the similarity scores between the two given latency. A two layer fusion approach is proposed to enhance the overall performance of the system to achieve near 1.401% Equal Error Rate (EER). We also introduce two additional modules to increase the flexibility of the proposed system. These modules aim to accommodate exceptional cases, for instance, when a legitimate user is unable to provide his or her normal typing pattern due to reasons such as hand injury.

Original language	English
Pages (from-to)	8618-8627
Number of pages	10
Journal	Expert Systems with Applications
Volume	37
Issue number	12
DOIs	https://doi.org/10.1016/j.eswa.2010.06.097
Publication status	Published - 2010 Dec

Bibliographical note

Funding Information:
This work was supported by the Korea Science and Engineering Foundation (KOSEF) through the Biometrics Engineering Research Center (BERC) at Yonsei University.

All Science Journal Classification (ASJC) codes

Engineering(all)
Computer Science Applications
Artificial Intelligence

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10.1016/j.eswa.2010.06.097

Cite this

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AB - This paper describes a novel technique to strengthen password authentication system by incorporating multiple keystroke dynamic information under a fusion framework. We capitalize four types of latency as keystroke feature and two methods to calculate the similarity scores between the two given latency. A two layer fusion approach is proposed to enhance the overall performance of the system to achieve near 1.401% Equal Error Rate (EER). We also introduce two additional modules to increase the flexibility of the proposed system. These modules aim to accommodate exceptional cases, for instance, when a legitimate user is unable to provide his or her normal typing pattern due to reasons such as hand injury.

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Keystroke dynamics in password authentication enhancement

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

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