A review on the public benchmark databases for static keystroke dynamics <s> BIOCHAVES{A,B,C} <s> The effect of parametric equalization of time interval histograms (key down-down intervals) on the performance of keystroke-based user verification algorithms is analyzed. Three 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, and a new one for arbitrary text based verification. Their performances are reported 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. <s> BIB001 </s> A review on the public benchmark databases for static keystroke dynamics <s> BIOCHAVES{A,B,C} <s> 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. <s> BIB002 </s> A review on the public benchmark databases for static keystroke dynamics <s> BIOCHAVES{A,B,C} <s> Identity verification through fusion of features from keystroke dynamics and speech is addressed in this paper. We experimentally compare performances from identity verification algorithms based on fusion of median pitch (prosodic level information), mel-frequency cepstral coefficients (short-time spectral level information) and keystroke dynamics (down-down intervals). These experimental results are also compared to the corresponding unimodal performances. All experiments are carried out on a small but true multimodal public database. Three fusion strategies are experimentally compared. A nonnegligeable performance improvement is then observed, mainly with a simple linear fusion strategy based on fusion of estimates. <s> BIB003
The biochaves team has used the same KDB in several papers BIB001 BIB002 BIB003 . There are 3 sub-datasets (A, B, C) for static-text and 1 dataset (D) for freetext  . The maximum number of users in a dataset is 15 and the number of provided samples per user is 10. Each dataset contains the raw data of some users providing 10 samples. It seems that users are different among the datasets. The dataset is composed of couples of ASCII codes of the pressed key and the elapsed time since the last key down event. Release of a key is not tracked. Each dataset is stored in raw text files.