| Title: | Alghamdi S.J. and Lamiaa A. Elrefaei, “Effect of Training Data Size on Touch Keystroke Verification with Medians Vector Proximity Classifier”, International Journal of Simulation- Systems, Science and Technology- IJSSST, Vol. 16, No. 6,2015, DOI: 10.5013/IJSSST.a.16.06.04. |
| Authors: | Alghamdi S.J. and Lamiaa A. Elrefaei |
| Year: | 2015 |
| Keywords: | Not Available |
| Journal: | Not Available |
| Volume: | Not Available |
| Issue: | Not Available |
| Pages: | Not Available |
| Publisher: | Not Available |
| Local/International: | International |
| Paper Link: | |
| Full paper | Not Available |
| Supplementary materials | Not Available |
| Abstract: |
This paper presents a user verification system on mobile phones that is based on keystroke dynamics derived from a touchable keyboard. The touch keystroke dynamics dataset are collected using a developed mobile application in which, unlike other systems, no specific text is required. Two scenarios were considered: few-training and more-training datasets. The Median Vector Proximity classifier is applied on both datasets and the performance of the system is investigated using a different number of features. Using few-training dataset, the average EER were 12.9% and 12.2% for 31 and 33 features respectively. Using more- training dataset brings improved results with EER=0.76% and EER=0.39% for 31 and 33 features respectively. The Medians Vector Proximity becomes more accurate when increasing the training data. Also, using more features reduced the average EER by 0.7% and 0.37% in few-training and more-training datasets respectively. The proposed system is compared against other systems and shows promising results. |
