Keystroke authentication is a new access control system to identify legitimate users via their typing behavior. Here, the machine learning techniques have been adapted for the purpose of authentication. The differnt keystroke patterns of the user are created using seven different models and is used to differentiate between the users. Decision Tree, Naive Bayesian, Instance Based Learning, Decision Table, One Rule, Random Tree and K-star etc are the learning methods used for this purpose.
access request, information extraction and authenticating are the three processes involved in the authenticating of a user. The dominant form of authentication nowadays is the Textual based authentication system. But this is a weak system with a high risk of information leak. The Biometric authentication systems is expected to have a better scalability. “physiological biometric” and “behavioral biometrics" are the two different types of biometric technologies used, of which the behavioral biometrics is more flexible. The typical behavioral biometric characteristics include the voice tune and typing pattern.
The authentication using the typing pattern detection is based on the fact that individuals type in a characteristic way on a keyboard.

For more details see:
http://wasetjournals/ijmcs/v1/v1-3-27.pdf
http://bibliotecadigital.sbc.org.br/down...?paper=319