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Sensors (Basel). 2017 Sep 6;17(9). pii: E2043. doi: 10.3390/s17092043.

Authentication of Smartphone Users Based on Activity Recognition and Mobile Sensing.

Author information

1
Faculty of Telecom and Information Engineering, University of Engineering and Technology, Taxila, Punjab 47050, Pakistan. ehatishamuet@gmail.com.
2
Faculty of Telecom and Information Engineering, University of Engineering and Technology, Taxila, Punjab 47050, Pakistan. awais.azam@uettaxila.edu.pk.
3
School of Computing and Engineering, University of West London, London W5 5RF, UK. yasar.amin@uettaxila.edu.pk.
4
State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China. shuangk@bupt.edu.cn.
5
School of Architecture, Computing and Engineering, University of East London, London E16 2RD, UK. syed.islam@uel.ac.uk.
6
School of Architecture, Computing and Engineering, University of East London, London E16 2RD, UK. u.naeem@uel.ac.uk.
7
Faculty of Telecom and Information Engineering, University of Engineering and Technology, Taxila, Punjab 47050, Pakistan. jonathan.loo@uwl.ac.uk.

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.

KEYWORDS:

activity recognition; behavioral biometrics; continuous sensing; micro-environment sensing; mobile sensing; smartphone authentication; ubiquitous computing

PMID:
28878177
PMCID:
PMC5620999
DOI:
10.3390/s17092043
[Indexed for MEDLINE]
Free PMC Article

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