|
ABSTRACT
Unlike other access control systems based on biometric features, keystroke analysis has not led to techniques providing an acceptable level of accuracy. The reason is probably the intrinsic variability of typing dynamics, versus other---very stable---biometric characteristics, such as face or fingerprint patterns. In this paper we present an original measure for keystroke dynamics that limits the instability of this biometric feature. We have tested our approach on 154 individuals, achieving a False Alarm Rate of about 4% and an Impostor Pass Rate of less than 0.01%. This performance is reached using the same sampling text for all the individuals, allowing typing errors, without any specific tailoring of the authentication system with respect to the available set of typing samples and users, and collecting the samples over a 28.8-Kbaud remote modem connection.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
| |
1
|
|
| |
2
|
Ashbourn, J. 2000b. The distinction between authentication and identification. Paper available at the Avanti Biometric Reference Site. (homepage.ntlworld.com/avanti)
|
| |
3
|
Axelsson, S. 2000a. Intrusion detection systems: A taxonomy and survey. Tech. Rep: 99-15. Dept. Computer Engineering, Chalmer University of Technology, Sweden, March. Paper available at www.ce.chalmers.se/staff/sax/taxonomy.ps.
|
 |
4
|
|
| |
5
|
|
| |
6
|
|
| |
7
|
Brown, M. E. and Rogers, S. J. 1996. Method and apparatus for verification of a computer user's identification, based on keystroke characteristics. Patent Number 5,557,686, U.S. Patent and Trademark Office, Washington, D.C., Sept.
|
| |
8
|
Burton, M. C. 2001. The value of web log data in use-based design and testing. J. Comput. Med. Commun. 6, 3. Also available at: www.ascusc.org/jcmc/vol6/issue3/burton.html
|
| |
9
|
Commun. ACM, Special issue on Personalization. Volume 43, Number 8. 2000.
|
| |
10
|
|
| |
11
|
S. M. Furnell , J. P. Morrissey , P. W. Sanders , C. T. Stockel, Applications of keystroke analysis for improved login security and continuous user authentication, Information systems security: facing the information society of the 21st century, Chapman & Hall, Ltd., London, UK, 1996
|
| |
12
|
Gaines, R., Lisowski, W., Press, S., and Shapiro, N. 1980. Authentication by keystroke timing: Some preliminary results. Rand. Report R-256-NSF. Rand Corporation.
|
| |
13
|
Garcia, J. 1986. Personal identification apparatus. Patent Number 4,621,334, U.S. Patent and Trademark Office, Washington, D.C., Nov.
|
 |
14
|
|
| |
15
|
|
| |
16
|
|
| |
17
|
D. Mahar , R. Napier , M. Wagner , W. Laverty , R. D. Henderson , M. Hiron, Optimizing digraph-latency based biometric typist verification systems: inter and intra typist differences in digraph latency distributions, International Journal of Human-Computer Studies, v.43 n.4, p.579-592, Oct. 1995
[doi> 10.1006/ijhc.1995.1061]
|
 |
18
|
|
 |
19
|
|
 |
20
|
|
| |
21
|
Obaidat, M. S. and Macchairolo, D. T. 1994. A multilayer neural network system for computer access security. IEEE Trans. Syst. Man, and Cybernet. Part B: Cybernet. 24, 5, 806--812.
|
| |
22
|
|
| |
23
|
Obaidat, M. S. and Sadoun, B. 1997b. Verification of computer users using keystroke dynamics. IEEE Trans. Syst. Man, and Cybernet. Part B: Cybernet. 27, 2, 261--269.
|
| |
24
|
|
 |
25
|
|
| |
26
|
|
| |
27
|
Polemi, D. 2000. Biometric techniques: review and evaluation of biometric techniques for identification and authentication, including an appraisal of the areas where they are most applicable. Report prepared for the European Commission DG XIII-C.4 on the Information Society Technologies (IST) (Key action 2: New Methods of Work and Electronic Commerce). Report available at: www.cordis.lu/infosec/src/stud5fr.html.
|
 |
28
|
|
| |
29
|
Vora, P., Reynolds, D., Dickinson, I., Erickson, J., and Banks, D. 2001. Privacy and Digital Rights Management. World Wide Web Consortium Workshop on Digital Rights Management for the Web. Also available at: www.w3.org/2000/12/drm-ws/pp/hp-poorvi.html.
|
| |
30
|
Umphress, D. and Williams, G. 1985. Identity verification through keyboard characteristics. Internat. J. Man-Mach. Stud. 23, 263--273.
|
| |
31
|
Young, J. R. and Hammon, R. W. 1989. Method and Apparatus for Verifying an Individual's Identity. Patent Number 4,805,222, U.S. Patent and Trademark Office, Washington, D.C., Feb.
|
CITED BY 6
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Kenneth Revett , Florin Gorunescu , Marina Gorunescu , Marius Ene , Sergio Tenreiro de Magalhaes , Henrique M. Dinis Santos, A machine learning approach to keystroke dynamics based user authentication, International Journal of Electronic Security and Digital Forensics, v.1 n.1, p.55-70, May 2007
|
|
|
|
REVIEW
"Jonathan K. Millen : Reviewer"
The phrase “keystroke dynamics” in the title of this paper refers to the time intervals between keypress events. The advantage of using keystroke dynamics to identify users is that they can be collected from an ordinary keyboard, and t
more...
|