"Misuse detection for mobile devices using behaviour profiling" by Fudong Li, Nathan Clarke et al.
 

Misuse detection for mobile devices using behaviour profiling

Document Type

Journal Article

Publisher

IGI Global

Faculty

Faculty of Computing, Health and Science

School

School of Computer and Security Science / Security Research Centre (secAU)

RAS ID

12831

Comments

Li, F., Clarke, N. , Papadaki, M., & Dowland, P. (2011). Misuse Detection for Mobile Devices Using Behaviour Profiling. International Journal of Cyber Warfare and Terrorism, 1(1), 43-55. Available here

Abstract

Mobile devices have become essential to modern society; however, as their popularity has grown, so has the requirement to ensure devices remain secure. This paper proposes a behaviour-based profiling technique using a mobile user’s application usage to detect abnormal activities. Through operating transparently to the user, the approach offers significant advantages over traditional point-of-entry authentication and can provide continuous protection. The experiment employed the MIT Reality dataset and a total of 45,529 log entries. Four experiments were devised based on an application-level dataset containing the general application; two application-specific datasets combined with telephony and text message data; and a combined dataset that included both application-level and application-specific. Based on the experiments, a user’s profile was built using either static or dynamic profiles and the best experimental results for the application-level applications, telephone, text message, and multi-instance applications were an EER (Equal Error Rate) of 13.5%, 5.4%, 2.2%, and 10%, respectively.

DOI

10.4018/ijcwt.2011010105

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Link to publisher version (DOI)

10.4018/ijcwt.2011010105

 
 
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