Paper Info
Title
Identifying Smartphone Users based on their Activity Patterns via Mobile Sensing.
Abstract
Smartphones are ubiquitous devices that enable users to perform many of their routine tasks anytime and anywhere. With the advancement in information technology, smartphones are now equipped with sensing and networking capabilities that provide context-awareness for a wide range of applications. Due to ease of use and access, many users are using smartphones to store their private data, such as personal identifiers and bank account details. This type of sensitive data can be vulnerable if the device gets lost or stolen. The existing methods for securing mobile devices, including passwords, PINs and pattern locks are susceptible to many bouts such as smudge attacks. This paper proposes a novel framework to protect sensitive data on smartphones by identifying smartphone users based on their behavioral traits using smartphone embedded sensors. A series of experiments have been conducted for validating the proposed framework, which demonstrate its effectiveness.
Year
DOI
Venue
2017
10.1016/j.procs.2017.08.349
Procedia Computer Science
Keywords
Field
DocType
Activity Recognition,Behavioral Biometrics,Continuous Sensing,Mobile Device Security,Data Privacy,Mobile Sensing,Ubiquitous Computing,User Identification
Data mining,Activity recognition,Identifier,Computer science,Usability,Mobile device,Password,Ubiquitous computing,Information privacy,Information and Computer Science
Conference
Volume
ISSN
Citations 
113
1877-0509
2
PageRank 
References 
Authors
0.38
17
5
Name
Order
Citations
PageRank
Muhammad Ehatisham-ul-Haq1276.73
Muhammad Awais Azam217824.45
Usman Naeem311615.31
Shafiq Ur Réhman428429.26
Asra Khalid5343.54