Identifying Smartphone Users based on their Activity Patterns via Mobile Sensing
Ehatisham-ul-Haq, M., Azam, Muhammad Awais, Naeem, U., Rѐhman, Shafiq Ur and Khalid, Asra 2017. Identifying Smartphone Users based on their Activity Patterns via Mobile Sensing. Procedia Computer Science. 113, pp. 202-209.
|Authors||Ehatisham-ul-Haq, M., Azam, Muhammad Awais, Naeem, U., Rѐhman, Shafiq Ur and Khalid, Asra|
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.
|Journal||Procedia Computer Science|
|Journal citation||113, pp. 202-209|
|Digital Object Identifier (DOI)||doi:10.1016/j.procs.2017.08.349|
|Web address (URL)||https://doi.org/10.1016/j.procs.2017.08.349|
|19 Sep 2017|
|Publication process dates|
|Deposited||05 Oct 2017|
|Copyright information||© 2017 The Authors.|
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