Abstract： In order to improve the recognition accuracy of key stroke authentication, a methodology based on feature extraction of keystroke sequence is presented in this paper. Firstly, the data of the users＇ keystr...Abstract： In order to improve the recognition accuracy of key stroke authentication, a methodology based on feature extraction of keystroke sequence is presented in this paper. Firstly, the data of the users＇ keystroke feature information that has too much deviation with the mean deviation is filtered out. Secondly, the probability of each input key is calculated and 10 values which do not have the best features are selected. Thirdly, they are weighed and a score evaluating the extent to which the user could be authenticated successfully is calculated. The benefit of using a third-party data set is more objective and comparable. At last,展开更多
基金This paper has been performed in the Project "Key Technology Research of Eavesdropping Detection in the Quantum Security Communication" supported by the National Natural Science Foundation of China
文摘Abstract： In order to improve the recognition accuracy of key stroke authentication, a methodology based on feature extraction of keystroke sequence is presented in this paper. Firstly, the data of the users＇ keystroke feature information that has too much deviation with the mean deviation is filtered out. Secondly, the probability of each input key is calculated and 10 values which do not have the best features are selected. Thirdly, they are weighed and a score evaluating the extent to which the user could be authenticated successfully is calculated. The benefit of using a third-party data set is more objective and comparable. At last,
