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Design and Implementation of User Authentication Based on Keystroke DynamicHsin, Tsung-Chin 28 January 2008 (has links)
In the traditional login systems, we use the username and the password to identify the legalities of users. It is a simple and convenient way to identify, but passwords could be stolen or copied by someone who tries to invade the system illegally. Adding one protective mechanism to identify users, the way of biometrics are brought out, such as keystroke dynamics, fingerprints, DNA, retinas and so on that are unique characteristics of each individuals, it could be more effective in preventing trespassing. This thesis uses keystroke biometrics as research aspects of user authentication. The advantages of this system are low-cost and high security to identify users using keyboard to calculate the time of keystrokes. In this thesis, we use statistical way to examine the researches and experiments. Chosen length of the username and password are greater than or equal to 9 characters, and learning sample sizes are 20 and adapting the sample adaptation mechanism, the results show that we achieved by False Acceptance Rate of 0.85%, False Rejection Rate of 1.51% and Average False Rate of 1.18%; all reach the high levels of safeties.
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A Comparison of Three Verification Methods for Keystroke DynamicChen, Hsiao-ying 11 February 2009 (has links)
In login systems, a user is asked to enter his correct account and password
in order to be allowed to enter to the system. The safety of systems is at the
risk of leaking out the information, hence, the single mechanism of identity
verification has not filled the bill at present. We study the personal typing
behavior to get one¡¦s own specific features.
In our thesis , we compare three methods and anlysis the advantages and
shortcomings of those three. First one is to sort the twenty study data, and
distribute the weights into the proper region. If the total weights is less than
the threshold then this test data will be accepted, otherwise, it will be rejected.
The second and third method are similar. Both of them are trying to rescale
the data. The spirit of them is that the typing rate of a person will be faster
when they type frequently and will be sloer when they are out of practice.
However the relative positions of those keys, the lengths of ons¡¦s fingers, and
the time that people making pauses in reading unpunctuated are unique.
Those factors can be one¡¦s typing rhythm.
There are twenty two individuals involved in this experiment. Each one
choose his own proficient account and password to type and set up his typing
model. The imposters are randomly choose legal user to imitate.
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