WEBVTT

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My name is Erik Ferragut.

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I'm an applied research mathematician

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at Oak Ridge National Laboratory.

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CPAD is a technology

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for detecting real-time cyber-physical

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integrity attacks

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in your system using data

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that you are already collecting.

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The problem of data integrity is

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something that you see across lots

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of cyber-physical systems.

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Our technology uses machine learning

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to look across the variety of sensors

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in a cyber-physical system.

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We then learn the relationships among

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those sensors, the correlations

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and constraints that have to hold.

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And using that model that we build,

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we can apply it to real streaming data

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to alert whenever there's a deviation

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from what has to hold

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in the physically realizable state.

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Our approach to detecting integrity

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attacks is different because we look

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across all of the sensors and are able

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to use those correlations to identify

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when there's a deviation from normal.

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Compared to other methods,

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we found we can get 30 plus times

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as accurate in identifying whether there

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was an attack and where in your system

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that attack occurred.

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We've tested this on both simulated

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and real data and found 99 percent

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accuracy in the simulated data,

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87 percent accuracy in the real data,

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and we're still working on ways

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of improving that.

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CPAD allows you

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to do real-time data integrity attack

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detection on your cyber-physical system.

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And you can do it

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with data you're already collecting.