Behaviour profiling on mobile devices

Fudong Li*, Nathan Clarke, Maria Papadaki, Paul Dowland

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceedings published in a bookpeer-review

Abstract

Over the last decade, the mobile device has become a ubiquitous tool within everyday life. Unfortunately, whilst the popularity of mobile devices has increased, a corresponding increase can also be identified in the threats being targeted towards these devices. Security countermeasures such as AV and firewalls are being deployed; however, the increasing sophistication of the attacks requires additional measures to be taken. This paper proposes a novel behaviour-based profiling technique that is able to build upon the weaknesses of current systems by developing a comprehensive multilevel approach to profiling. In support of this model, a series of experiments have been designed to look at profiling calling, device usage and Bluetooth network scanning. Using neural networks, experimental results for the aforementioned activities' are able to achieve an EER (Equal Error Rate) of: 13.5%, 35.1% and 35.7%.

Original languageEnglish
Title of host publicationProceedings - EST 2010 - 2010 International Conference on Emerging Security Technologies, ROBOSEC 2010 - Robots and Security, LAB-RS 2010 - Learning and Adaptive Behavior in Robotic Systems
Pages77-82
Number of pages6
DOIs
Publication statusPublished - 2010
Event2010 International Conference on Emerging Security Technologies, EST 2010, Robots and Security, ROBOSEC 2010, Learning and Adaptive Behavior in Robotic Systems, LAB-RS 2010 - Canterbury, United Kingdom
Duration: 6 Sept 20108 Sept 2010

Publication series

NameProceedings - EST 2010 - 2010 International Conference on Emerging Security Technologies, ROBOSEC 2010 - Robots and Security, LAB-RS 2010 - Learning and Adaptive Behavior in Robotic Systems

Conference

Conference2010 International Conference on Emerging Security Technologies, EST 2010, Robots and Security, ROBOSEC 2010, Learning and Adaptive Behavior in Robotic Systems, LAB-RS 2010
Country/TerritoryUnited Kingdom
CityCanterbury
Period6/09/108/09/10

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Control and Systems Engineering

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