Statistical three-class user authentication approach based on user''''s keystroke patterns
基于三分类的击键序列身份认证

In order to overcome the deficiency of low veracity of the current user authentication approach based on statistics,a new user authentication approach based on keystroke sequences was proposed.The proposed approach classified the current registered users into three groups: intrusive,suspicious and normal according to the dispersion between the user's keystroke pattern and the standard model determined by training samples and then utilized a re-recognition process to identify the user belonging to the suspicious group.The parameter k related to the security and friendliness level was introduced,which can be dynamically determined by supervisors of hosts.The performance of the proposed approach was evaluated by experiments and theoretical analyses.The results show the superiority of the proposed approach in terms of the False Rejection Rate(FRR) and False Acceptance Rate(FAR) in comparison with current Bayesian method,and the FRR and FAR of the proposed approach is only 1.6% and 1.5% respectively.