Sensor-based Continuous Authentication of Smartphones' Users Using
Behavioral Biometrics: A Survey
release_b2rjjapeizhmvmspmu3dytxg2y
by
Mohammed Abuhamad, Ahmed Abusnaina, DaeHun Nyang, David Mohaisen
2020
Abstract
Mobile devices and technologies have become increasingly popular, offering
comparable storage and computational capabilities to desktop computers allowing
users to store and interact with sensitive and private information. The
security and protection of such personal information are becoming more and more
important since mobile devices are vulnerable to unauthorized access or theft.
User authentication is a task of paramount importance that grants access to
legitimate users at the point-of-entry and continuously through the usage
session. This task is made possible with today's smartphones' embedded sensors
that enable continuous and implicit user authentication by capturing behavioral
biometrics and traits. In this paper, we survey more than 140 recent behavioral
biometric-based approaches for continuous user authentication, including
motion-based methods (27 studies), gait-based methods (23 studies), keystroke
dynamics-based methods (20 studies), touch gesture-based methods (29 studies),
voice-based methods (16 studies), and multimodal-based methods (33 studies).
The survey provides an overview of the current state-of-the-art approaches for
continuous user authentication using behavioral biometrics captured by
smartphones' embedded sensors, including insights and open challenges for
adoption, usability, and performance.
In text/plain
format
Archived Files and Locations
application/pdf 493.2 kB
file_ajo7msc5uzc4hi7fhzl2odxbmy
|
arxiv.org (repository) web.archive.org (webarchive) |
2001.08578v1
access all versions, variants, and formats of this works (eg, pre-prints)