Abstract
<p><strong>Abstract</strong> - <strong>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.</strong></p>
Highlights
The widely usage of smartphones makes them one of a frequent storage medium for the users' sensitive information such as personal data, email, and credit card numbers/passwords
The results show that Movement Time (MT) has the least discrimination power, which can be mainly due to how quickly the users perform the task, as this feature needs more investigation in experiment
The results prove that the Finger Pressure (FP) and Signature Precision (SP) have increased the influence on accuracy for the combined features, this is because the MT has influenced negatively on the accuracy as mentioned early in the individually features section regarding the MT influence
Summary
The widely usage of smartphones makes them one of a frequent storage medium for the users' sensitive information such as personal data, email, and credit card numbers/passwords. The methods used to unlock screens can be categorized as the most current access systems prompt for users to authenticate themselves such as: text-based password, graphical based password, or grid-based schemes [14]. This authentication method relies on the password /username’s secrecy. The problems of user authentication associated with the integrity information that consists of maintaining password secrecy are well understood. Passwords that consist of common words, or terms associated with a particular user are generally considered weak because of the relative ease with which malicious users can guess them [13] and [21]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Interactive Mobile Technologies (iJIM)
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
