Term of Award

Spring 2019

Degree Name

Master of Science in Computer Science (M.S.)

Document Type and Release Option

Thesis (restricted to Georgia Southern)

Copyright Statement / License for Reuse

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Department

Department of Computer Science

Committee Chair

Ray Hashemi

Committee Member 1

Amar Rasheed

Committee Member 2

Hong Zhang

Abstract

The Internet of Things (IoT) is, simply put, the concept of connecting any network enabled device to the internet and/or to each other. These IoT connected devices include household appliances, security cameras, health care monitoring systems etc. As IoT devices become smaller and more complex, identifying possible security threats has become a more resource intensive process. However, IoT devices have a limited amount of on-board resource capacity which must be utilized to perform ever-growing complex functions of the device. In other words, as functionally goes up security goes down. This security concern is amplified by the fact that IoT devices gather more and more sensitive data in regard to their users. Historically, device security has involved complex software systems which require massive amounts of system resource to run as well as a constant series of updates to identify new threats. This historical approach is not a viable solution for resource constrained data driven IoT devices. It is the goal of this study to: (a) identify IoT device sensory inputs with specific characteristics of interest, (b) introduce a novel approach for enhancing an IoT device’s security by building unique device-specific profiles based on sensory inputs, and (c) examine the potential use of such a profile for threat detection in IoT devices. To accomplish all three prongs of the goal a needed framework wasimplemented, and a viable authentication protocol was established. The research concluded by identifying two sensory inputs (power consumption and execution time) which possess the specific characteristics needed for device profiling. The identified sensory inputs were then used to create an IoT device-specific profile which can be used to enhance device security.

OCLC Number

1101902989

Research Data and Supplementary Material

No

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