Last modified: 2020-12-26
Abstract
In this paper we offer a parametric method of training of biometric access control systems. This method is based on building separating surfaces between "legal" and "illegal" area on the base of the determination of unknown average of the legal user biometric parameters normal distribution.
Keywords
References
1. Ivanov A.I. "Personal biometric authentication using dynamics of subconscious motions". Penza state univ., Penza, Russia, 2000.
2. Monrose F., Rubin A.D. "Keystroke dynamics as a biometric for authentication". Future Generation Computer System, 2000; 16: 351-359.
3. Bryukhomitsky Yu.A., Kazarin M.N. 'A system of user authentication based on his handwriting". In: Proc. "Information security " conference. TSURE, Taganrog, Russia, 2002, pp. 22-29.
4. Bryukhomitsky Yu.A., Kazarin M.N. "A method of biometric user authentication with keystroke dynamics based on Haar transform and Hamming similarity measure". TSURE News, TSURE, Taganrog, Russia, 2003; 4(33): 141-149.
5. Brown M., Rogers S.J. "User identification via keystroke characteristics of typed names using neural networks". International Journal of Man-Machine Studies, 1993; 39(6): 999-1014.
6. Nilsson N.J. "Learning machines". McGraw-Hill Book Company, 1965.