Contribution to Book
Masquerade Detection on Mobile Devices
Guide to Vulnerability Analysis for Computer Networks and Systems: An Artificial Intelligence Approach
(2018)
Abstract
A masquerade is a type of attack where an intruder attempts to avoid detection by impersonating an authorized user of a system. In this research, we consider the problem of masquerade detection on mobile devices. Specifically, we experiment with a variety of machine learning techniques to determine how accurately we can distinguish mobile users, based on various features. Here, our primary goal is to determine which techniques are most likely to be effective in a more comprehensive masquerade detection system.
Disciplines
Publication Date
September 5, 2018
Editor
Simon Parkinson, Andrew Crampton, Richard Hill
Publisher
Springer
DOI
10.1007/978-3-319-92624-7_13
Citation Information
Swathi Nambiar Kadala Manikoth, Fabio Di Troia and Mark Stamp. "Masquerade Detection on Mobile Devices" Guide to Vulnerability Analysis for Computer Networks and Systems: An Artificial Intelligence Approach (2018) p. 301 - 315 Available at: http://works.bepress.com/mark_stamp/49/