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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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Host title:
The Network and Distributed System Security Symposium (NDSS)
Publication date:
2015-02-01
UUID:
uuid:6dd4bf7a-be17-4048-ac5b-7d4447c004e9
Local pid:
cs:9137
Deposit date:
2015-03-31

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