A correlation method for handling infrequent data in keystroke biometric systems
Steve Kim, Sung-Hyuk Cha, John Vincent Monaco, Charles C. Tappert · 2014
Many applications need methods for handling missing or insufficient data. This paper applies a correlation technique to improve the fallback methods previously used to handle the paucity of keystroke data from the infrequently used keys in a keystroke biometric system. The proposed statistical fallback model uses a correlation based fallback table based on the linear correlation between pairs of keys. Two large long-text keystroke databases are used in the study - one to construct the model and the other to evaluate system performance as a function of sample length.