User authentication algorithm with keystroke features based on genetic algorithms and grey relational analysis
基于遗传算法和灰色关联分析的击键特征识别算法

User authentication based on keystroke dynamics features is more secure than conventional user authentication approach only based on passwords.The neural network and data mining-based methods present high authentication accuracy,but have a high computational cost.The statistical and vector-based methods have shown low computational complexity,but are less accurate in user authentication.In order to improve authentication accuracy and reduce computational complexity synchronously,a new user authentication approach based on keystroke patterns was proposed.In the proposed approach,Genetic algorithm was employed to generate the common keystroke pattern of each user from the training set consisting of the user's normal keystroke samples.Then Grey Relational analysis method was applied to calculate the degree of grey slope incidence between common keystroke pattern and current keystroke pattern,the resultant value was compared with a threshold value determined by experiment to implement user authentication.Experimental results show this approach represents the same user authentication accuracy as neural network and data mining-based methods in terms of False Acceptance Rate(FAR) and False Rejection Rate(FRR),false acceptance rate and false rejection rate of this method are 1.5% and 0% respectively.It is also shows that the computational complexity of the proposed method is lower than that of some other methods.