• home
• current students
• graduate
• events

Presenter: Faisal Alshanketi
Supervisor:

Date: Tue, August 14, 2018
Time: 11:00:00 - 12:00:00
Place: EOW 430

ABSTRACT

Abstract

With the progress achieved to this date in mobile computing technologies,

mobile devices   are increasingly being used to store sensitive data and

perform security-critical transactions and services. However, the protection available on these devices is still lagging behind. The primary and often only protection mechanism in these devices is authentication using a password or a PIN. Passwords are notoriously known to be a weak authentication mechanism, no matter how complex the underlying format is.

Mobile authentication can be strengthened by extracting and analyzing keystroke dynamic biometric from supplied passwords. In this seminar, we identify gaps in the literature, and investigate new models and mechanisms for improving accuracy and usability of mobile keystroke dynamic biometric authentication. Accuracy is investigated through cost sensitive learning and sampling, and by comparing the strength  of different classifiers.

Usability is improved by introducing a new approach for typo handling in the authentication model. Experimental evaluation is conducted using 3 different datasets, two public and one collected in our lab, yielding very encouraging results.