User Identification Based on the Dynamic Features Extracted from Handwriting on Touchscreen Devices

User Identification Based on the Dynamic Features Extracted from Handwriting on Touchscreen Devices

User identification

user identification on smartphone

security on smartphone

Dynamic time warping

dynamic features

mobile computing

and handwriting based finger on smartphone.

Abstract - This research presents a methodology for user identification using ten English words written by a finger on smartphone and mini-tablet. This research considers three features, namely Signature Precision (SP), Finger Pressure (FP), and Movement Time (MT) that were extracted from each of ten English words using dynamic time warping. The features are then used individually and combined for the purpose of user identification based on the Euclidean distance and the k-nearest neighbor classifier. We concluded that the best identification accuracy results from the combinations of (SP and FP) features with an average accuracies of 74.55% and 69% were achieved on small smartphone and Mini-tablet respectively using a dataset of 42 users.

Al-Showarah, Suleyman

Alzyadat, Wael

Alhroob, Aysh

Al-Assam, Hisham

International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 11 (2020); pp. 126-136

1865-7923

International Association of Online Engineering (IAOE), Vienna, Austria

2020-07-10

Copyright (c) 2020 Suleyman AlShowarah, Hisham Al-Assam

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eng

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info:eu-repo/semantics/publishedVersion

Peer-reviewed Article