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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01b2773z31z
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dc.contributor.advisorKpotufe, Samory K.-
dc.contributor.authorChiang, Michael-
dc.date.accessioned2017-07-19T18:23:53Z-
dc.date.available2017-07-19T18:23:53Z-
dc.date.created2017-04-17-
dc.date.issued2017-4-17-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01b2773z31z-
dc.description.abstractInternet of Things (IoT) devices are becoming more prevalent in our world with the rise of products like the Nest Thermostat and the Amazon Echo. As these devices become more common and widespread, there is a larger risk of the device being used maliciously. The goal of this thesis is to determine whether an IoT device is active or idle using anomaly detection techniques. Solving this subproblem is an important first step in potentially being able to detect if an IoT device is being used maliciously.en_US
dc.language.isoen_USen_US
dc.titleApplications of Anomaly Detection: Activity Classification for IoT Devicesen_US
dc.typePrinceton University Senior Theses-
pu.date.classyear2017en_US
pu.departmentOperations Research and Financial Engineeringen_US
pu.pdf.coverpageSeniorThesisCoverPage-
pu.contributor.authorid960871104-
pu.contributor.advisorid961116620-
Appears in Collections:Operations Research and Financial Engineering, 2000-2019

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