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Title: Clustering and Outlier Detection: Methods and Applications in Smart Home Networks
Authors: Davis, Erick
Advisors: Kpotufe, Samory
Department: Operations Research and Financial Engineering
Class Year: 2016
Abstract: We present a review of outlier detection techniques and attempt to find a consensus approach for defining an outlier. We then extensively explore device activity in smart home networks. We attempt to identify individual device network profiles and differentiate the behavior originating from device activities. This is formulated as a clustering problem. Device behavior is analyzed in the context of finding an appropriate outlier detection definition and approach.
Extent: 96 pages
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Operations Research and Financial Engineering, 2000-2017

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