Effects of text filtering on authentication performance of keystroke biometrics

Free text keystroke dynamics is a behavioral biometric that has the strong potential to offer unobtrusive and continuous user authentication. In free-text keystroke biometrics, users are free to type whatever they want to while still being authenticated. However, not all keystrokes from a user exhibit the same quality of stable patterns that can be used to differentiate them from others. The “unstable” keystrokes may originate from such activities as when the user is playing a computer game, or other sources of noisy or “gibberish” text. Our hypothesis is that some forms of text negatively impact keystroke dynamics-based user authentication, and thus, should be filtered out. This study investigates the impact of gibberish text on authentication performance through locating and removing gibberish text, and comparing the difference in authentication performance before and after the removal. We confirm the positive effect of text filtering on authentication performance, especially on the reduction of the false reject rate.