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Preventing lunchtime attacks: fighting insider threats with eye movement biometrics

Abstract:

We introduce a novel biometric based on distinctive eye movement patterns. The biometric consists of 21 features that allow us to reliably distinguish users based on differences in these patterns. We leverage this distinguishing power along with the ability to gauge the users’ task familiarity, i.e., level of knowledge, to address insider threats. In a controlled experiment we test how both time and task familiarity influence eye movements and feature stability, and how different subsets of f...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Publisher's version

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Publisher copy:
10.14722/ndss.2015.23203

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Department:
Oxford, MPLS, Computer Science
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Department:
Oxford, MPLS, Computer Science
Lenders, V More by this author
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Department:
Oxford, MPLS, Computer Science
Publisher:
Internet Society Publisher's website
Publication date:
2015-02-05
DOI:
Pubs id:
pubs:576193
URN:
uri:01d8ca27-a0cd-4256-8838-65725960734f
UUID:
uuid:01d8ca27-a0cd-4256-8838-65725960734f
Local pid:
pubs:576193
ISBN:
1-891562-38-X
Keywords:

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