Authors
Eremenko A.
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Degree
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PhD in Technique, Omsk State Transport University |
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E-mail
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4eremenko@gmail.com |
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Location
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Omsk |
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Articles
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Two-factor authentication of users of computer systems on remote server using the keyboard handwritingauthentication
server. The method of two-factor authentication of users of computer systems on the remote
server using personal biometric data is proposed. The method based on error-correcting coding and
other conversion of biometric data. The developed method is based on «fuzzy extractors» and allows
to store only fragments of biometric standard on the server and does not allow to restore the standard
if this fragments were stolen. As the biometric features of a person is proposed to use the keystroke
dynamics: duration of retention and the time intervals between keystrokes as a person type the passphrase
on the keypad. An original way to use information about the stability of biometric features is
proposed. The information about biometric features stability is used to choose the best ones for preparing
a cryptographic key and decrease errors of key generation. Also it is a part of a secret information
that storages on the server side and used in key recovery procedure. As a part of the future research
for «combining» and «subtraction» bit sequences of PRN code and biometric data for cryptographic
key generation it is planned to use fuzzy implication operation, adapting one of the fuzzy inference
algorithms (Tsukamoto, Sugeno, Mamdani, Larsen et al.)
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Generation of key sequences based on voice messagesThe problem of the generation of the key sequences on the basis of biometric data is described. Objective: To develop a method of generating a key sequence based on the subject of voice parameters with indicators of reliability and key length exceeding achieved. Two features spaces of human voice are proposed: dependent and independent of the uttered phrase. The methods of generating keys based on voice messages on the basis of fuzzy extractors using Hadamard or Bose — Chaudhuri — Hocquenghem error correcting codes are proposed. Also the ranking procedure of most stable features individual for each subject was proposed. The effectiveness of the proposed method was defined. The optimum methods for each proposed feature space have been found. These results are superior to previously achieved by generating a key sequence based on voice. Read more... Identification potential of keyboard handwriting considering vibration parameters and force keystrokesThe article considers the problem of data protection from unauthorized access by means of user identification
by keyboard handwriting. The estimation of informativeness of different features that characterize
the keyboard handwriting of subjects, including the dynamics of change in pressure when you
press the keys and keyboard settings vibration. The category of new features, based on using of wavelet
transform Daubechies D6 to function of the pressure fingers on the keys and keyboard functions of
vibration while typing, was proposed. The laws of distribution of basic and additional features of keyboard
handwriting were determined. To form the base of biometric samples a keyboard was designed
with the use of special sensors. The estimation of the correlation dependence of features was made. It is
determined that the correlation between basic features (temporal characteristics of keystrokes) and additional
features (pressure on the keys and the keyboard vibration) in more than 80% of cases is weak.
Thus, in the proposed new attributes contain information about the subject. An assessment of the probability
of identification errors based on the Bayesian strategy using the various features of the spaces was
made. It is found that additional features can reduce the average number of errors is more than 7 times.
Read more...
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