Research Article
Understanding Keystroke Dynamics for Smartphone Users Authentication and Keystroke Dynamics on Smartphones Built-In Motion Sensors
Table 1
Comparison of studies for keystroke dynamics. Motion data column indicates whether features from motion data are used or not.
| Authors | Year | Methodology | Motion data | Number of subjects | Number of training samples | Classifier | EER (%) |
| Clarke et al. [8] | 2003 | 4-digit PIN | X | 30 | 30 | Statistical | 11.3 |
| Clarke and Furnell [9] | 2007 | 4-digit PIN | X | 30 | 30 | Neural network | 8.5 |
| | | 6 alphabetic characters | | | | Neural network | 15.2 |
| Chang et al. [6] | 2012 | 3–6 thumbnails | X | 100 | 5 | Statistical | 6.9 |
| De Mendizabal- Vázquez et al. [10] | 2014 | 4-digit PIN | O | 80 | 3–9 | Euclidean distance | 20 |
| Zheng et al. [5] | 2014 | 4-digit PIN/ 8-digit PIN | O | 80 | 80 | Nearest neighbor distance | 3.65/ 4.45 |
| Samura et al. [7] | 2014 | 300 characters (approximately) | X | 43 | 5 | Weighted Euclidean distance + array disorder | 2.2 FAR, 4.6 FRR |
| Giuffrida et al. [11] | 2014 | 8-9 characters | O | 20 | 40 (approximately) | kNN () Manhattan weighted, kNN () Manhattan scaled weighted | 8 |
| Antal and Szabó [12] | 2015 | 10 characters | X | 42 | 2/3 of data | Manhattan distance | 12.9 |
| Chang et al. [13] | 2016 | 6-digit PIN 8-digit PIN 10-digit PIN | X | 100 | 100 | Statistical | 23 21 16 |
| Wu and Chen [14] | 2015 | 8-digit PIN | O | 100 | 500 | SVM | 0.556 |
| Buschek et al. [15] | 2015 | 6–8 characters | X | 28 | - | Probabilistic modeling | 21.02 |
| Dhage et al. [16] | 2015 | 10 characters | X | 15 | 10 | Statistical | 0.806 |
| Bond and Awad [17] | 2015 | 34 characters | X | 25 | - | Neural network | 9.3 |
| Teh et al. [18] | 2016 | 4-digit PIN 16-digit PIN | X | 50/150 | 7 | Gaussian estimation, -score matching function, standard deviation drift | 7.57 5.49 |
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