Enhanced Authentication System Performance Based on Keystroke Dynamics using Classification algorithms
Asma Salem, Ahmad Sharieh, Azzam Sleit, Riad Jabri · KSII Transactions on Internet and Information Systems · 2019
Nowadays, most users access internet through mobile applications.The common way to authenticate users through websites forms is using passwords; while they are efficient procedures, they are subject to guessed or forgotten and many other problems.Additional multi modal authentication procedures are needed to improve the security.Behavioral authentication is a way to authenticate people based on their typing behavior.It is used as a second factor authentication technique beside the passwords that will strength the authentication effectively.Keystroke dynamic rhythm is one of these behavioral authentication methods.Keystroke dynamics relies on a combination of features that are extracted and processed from typing behavior of users on the touched screen and smart mobile users.This Research presents a novel analysis in the keystroke dynamic authentication field using two features categories: timing and no timing combined features.The proposed model achieved lower error rate of false acceptance rate with 0.1%, false rejection rate with 0.8%, and equal error rate with 0.45%.A comparison in the performance measures is also given for multiple datasets collected in purpose to this research.