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.
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Kadala Manikoth, S.N., Di Troia, F., Stamp, M. (2018). Masquerade Detection on Mobile Devices. In: Parkinson, S., Crampton, A., Hill, R. (eds) Guide to Vulnerability Analysis for Computer Networks and Systems. Computer Communications and Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-92624-7_13
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DOI: https://doi.org/10.1007/978-3-319-92624-7_13
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