Title

Authenticating mobile phone users using keystroke analysis

Document Type

Journal Article

Publisher

Springer-Verlag

Faculty

Computing, Health and Science

School

School of Computer and Information Science, Centre for Security Research

RAS ID

4664

Comments

This article was originally published as: Clarke, N. L., & Furnell, S. M. (2007). Authenticating mobile phone users using keystroke analysis. International Journal of Information Security, 6(1), 1-14. Original available here

Abstract

Mobile handsets have found an important place in modern society, with hundreds of millions currently in use. The majority of these devices use inherently weak authentication mechanisms, based upon passwords and PINs. This paper presents a feasibility study into a biometric-based technique, known as keystroke analysis – which authenticates the user based upon their typing characteristic. In particular, this paper identifies two typical handset interactions, entering telephone numbers and typing text messages, and seeks to authenticate the user during their normal handset interaction. It was found that neural network classifiers were able to perform classification with average equal error rates of 12.8%. Based upon these results, the paper concludes by proposing a flexible and robust framework to permit the continuous and transparent authentication of the user, thereby maximising security and minimising user inconvenience, to service the needs of the insecure and evermore functional mobile handset.

DOI

10.1007/s10207-006-0006-6

 

Link to publisher version (DOI)

10.1007/s10207-006-0006-6