Equalization of keystroke timing histograms for improved identification performance

The effect of parametric equalization of time interval histograms (key down-down intervals) on the performance of keystroke-based user verification algorithms is analyzed. Four algorithms are used throughout this analysis: a classic one for static (structured) texts, a second one, also proposed in literature, for both static and arbitrary (free) text, a new one for arbitrary text based verification, and an algorithm recently proposed, where keystroke timing is indirectly addressed in order to compare user dynamics. The algorithms performances are presented before and after time interval histogram equalization, and the results corroborate with the hypothesis that the nonlinear memoryless time interval transform proposed here, despite its simplicity, can be a useful and almost costless building block in keystroke-based biometric systems.