Authentication of smartphone users based on activity recognition and mobile sensing

Ehatisham-ul-Haq, Muhammad, Azam, Muhammad Awais, Loo, Jonathan, Shuang, Kai, Islam, Syed, Naeem, Usman and Amin, Yasar (2017) Authentication of smartphone users based on activity recognition and mobile sensing. Sensors, 17 (9). p. 2043. ISSN 1424-8220

[img]
Preview
PDF
sensors-17-02043-v3.pdf - Published Version
Available under License Creative Commons Attribution.

Download (2MB) | Preview

Abstract

Smartphones are context-aware devices that provide a compelling platform for ubiquitous computing and assist users in accomplishing many of their routine tasks anytime and anywhere, such as sending and receiving emails. The nature of tasks conducted with these devices has evolved with the exponential increase in the sensing and computing capabilities of a smartphone. Due to the ease of use and convenience, many users tend to store their private data, such as personal identifiers and bank account details, on their smartphone. However, this sensitive data can be vulnerable if the device gets stolen or lost. A traditional approach for protecting this type of data on mobile devices is to authenticate users with mechanisms such as PINs, passwords, and fingerprint recognition. However, these techniques are vulnerable to user compliance and a plethora of attacks, such as smudge attacks. The work in this paper addresses these challenges by proposing a novel authentication framework, which is based on recognizing the behavioral traits of smartphone users using the embedded sensors of smartphone, such as Accelerometer, Gyroscope and Magnetometer. The proposed framework also provides a platform for carrying out multi-class smart user authentication, which provides different levels of access to a wide range of smartphone users. This work has been validated with a series of experiments, which demonstrate the effectiveness of the proposed framework.

Item Type: Article
Additional Information: © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Uncontrolled Keywords: activity recognition; behavioral biometrics; continuous sensing; micro-environment sensing; mobile sensing; smartphone authentication; ubiquitous computing
Subjects: Computing > Intelligent systems
Depositing User: Jonathan Loo
Date Deposited: 15 Sep 2017 12:07
Last Modified: 18 Sep 2017 09:30
URI: http://repository.uwl.ac.uk/id/eprint/3914

Downloads

Downloads per month over past year

Actions (login required)

View Item View Item

Menu