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http://arks.princeton.edu/ark:/88435/dsp011v53k041f
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 |
URI: | http://arks.princeton.edu/ark:/88435/dsp011v53k041f |
Type of Material: | Princeton University Senior Theses |
Language: | en_US |
Appears in Collections: | Operations Research and Financial Engineering, 2000-2020 |
Files in This Item:
File | Size | Format | |
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Davis_Erik_Thesis.pdf | 1.71 MB | Adobe PDF | Request a copy |
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