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Source: Ms. Noor Al-Obaidi, noor_mahmood_2012 '@' hotmail.com, Middle East University, Faculty of Information Technology, Amman, Jordan. Data Set Information: The dataset is used in the evaluation of EER, FRR and FAR metrics using a new anomaly detector model (Med-Min-Diff). The typed text in the experiment is the password '.tie5Roanl'. Attribute Information: The measured features (attributes) are Hold (H), Up-Down (UD), Down-Down (DD), Pressure (P), Finger-Area (A), Averages of Hold (AH), Pressure (AP) and Finger Area (AFA). There are 71 features because each feature has a set of feature elements corresponding to the typed characters.
Relevant Papers: 1. Master thesis from Middle East University in Jordan, May 2016 (A New Statistical Anomaly Detector Model for Keystroke Dynamics on Touch Mobile Devices)>
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