Abstract
The evolution of mobile networking has opened the door to a wide range of service opportunities for mobile devices, increasing at the same time the sensitivity of the information stored and access through them. Current PIN-based authentication has proved to be an insufficient and an inconvenient approach. Biometrics have proven to be a reliable approach to identity verification and can provide a more robust means of security, as they rely upon personal identifiers. Amongst various biometric techniques available, keystroke analysis combines features that can offer a cost effective, non-intrusive and continuous authentication solution for mobile devices. This research has been undertaken in order to investigate the performance of keystroke analysis on thumb-based keyboards that are being widely deployed upon PDA’s and Smartphone devices. The investigation sought to authenticate users whilst typing text messages, using two keystroke characteristics, the inter-keystroke latency and hold-time. The results demonstrate the approach to be promising, achieving an average EER=12.2% with the inter-keystroke latency based upon 50 participants. Uniquely to this tactile environment however, the hold-time characteristic, did not prove to be a reliable feature to be utilised.
Please use the following format when citing this chapter: Karatzouni, S. and Clarke, N., 2007, in IFIP International Federation for Information Proeessing, Volume 232, New Approaches for Security, Privacy and Trust in Complex Environments, eds. Venter, H., Eloff, M-, Labuschagne, L., ElofT, -I., von Solms. R., (Boston: Springer), pp. 253–263.
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References
The UTMS Forum, Mobile Evolution — Shaping the future (August 1, 2003); http://www.umts-forum.org/servlet/dycon/ztumts/umts/Live/en/umts/MultiMedia_PDFs_Papers_Paper-l-August-2003.pdf.
British Transport Police, Mobile phone theft (August 20, 2006); http://www.btp.police.uk/issues/mobile.htm.
R. Lemos, Passwords: The Weakest Link? Hackers can crack most in less than a minute, CNET.com, (2002), http://www.news.com.com/2009-1001-916719.html.
N. Clarke, S.M. Furnell, P.M. Rodwell, P.L. Reynolds, Acceptance of subscriber authentication method for mobile telephony devices, Computers & Security, 21(3), pp220–228, 2002.
Pointsec, IT professionals turn blind eye to mobile security as survey reveals sloppy handheld habits (November 17, 2005); http://www.pointsec.com/news/release.cfm?PressId=108.
R. Spillane, Keyboard Apparatus for personal identification, IBM Technical Disclosure Bulletin, 17(3346) (1975).
D. Umphress, G. Williams, Identity Verification through Keyboard Characteristics, Internationaljournal of Man-Machine Studies, 23, pp. 263–273 1985.
R. Joyce, G. Gupta, Identity Authentication Based on Keystroke Latencies, Communications of the ACM, 39, pp 168–176 1990.
M. Brown, J. Rogers, User Identification via Keystroke Characteristics of Typed Names using Neural Networks, International Journal of Man-Machine Studies, 39, pp. 999–1014(1993).
M. S. Obaidat, B. Sadoun, Verification of Computer User Using Keystroke Dynamics, IEEE Transactions on Systems, Man and Cybernetics — Part B: Cybernetics, 27(2), (1997).
T. Ord, User Authentication using Keystroke Analysis with a Numerical Keypad Approach, (MSc Thesis, University of Plymouth, UK, 1999).
NL. Clarke, S.M. Furnell, Authenticating Mobile Phone Users Using Keystroke Analysis, International Journal of Information Security, ISSN: 1615-5262, (2006), pp. 1–14.
13. G. Leggett, J. Williams, Verifying identity via keystroke characteristics, Internationaljournal of Man-Machine Studies, Vol. 28(1), (1988), pp. 67–76.
14. R. Napier, W. Laverty, D. Mahar, R. Henderson, M. Hiron, M. Wagner, Keyboard User Verification: Toward an accurate, Efficient and Ecological Valid Algorithm, International Journal of Human-Computer Studies, 43, pp. 213–222 (1995).
S. Cho, C. Han, D. Han, H. Kin, Web Based Keystroke Dynamics Identity Verification Using Neural Networks, Journal of Organizational Computing & Electronic Commerce, 10, pp. 295–307 (2000).
S. Haykin, Neural networks: A Comprehensive Foundation (2nd edition, (Prentice Hall, New Jersey, 1999).
M. Bishop, Neural Networks for Pattern Classification, (Oxford University Press, New York, 1995).
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Karatzouni, S., Clarke, N. (2007). Keystroke Analysis for Thumb-based Keyboards on Mobile Devices. In: Venter, H., Eloff, M., Labuschagne, L., Eloff, J., von Solms, R. (eds) New Approaches for Security, Privacy and Trust in Complex Environments. SEC 2007. IFIP International Federation for Information Processing, vol 232. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-72367-9_22
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DOI: https://doi.org/10.1007/978-0-387-72367-9_22
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