Princeton University Library Catalog

Applications of Anomaly Detection: Activity Classification for IoT Devices

Author/​Artist:
Chiang, Michael [Browse]
Format:
Senior thesis
Language:
English
Advisor(s):
Kpotufe, Samory K. [Browse]
Department:
Princeton University. Department of Operations Research and Financial Engineering [Browse]
Class year:
2017
Summary note:
Internet 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.