DOI

https://doi.org/10.25772/BZJZ-P234

Author ORCID Identifier

https://orcid.org/0000-0002-3463-7232

Defense Date

2018

Document Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Computer Science

First Advisor

Thang N. Dinh, PhD.

Abstract

The study of networks has seen a tremendous breed of researches due to the explosive spectrum of practical problems that involve networks as the access point. Those problems widely range from detecting functionally correlated proteins in biology to finding people to give discounts and gain maximum popularity of a product in economics. Thus, understanding and further being able to manipulate/control the development and evolution of the networks become critical tasks for network scientists. Despite the vast research effort putting towards these studies, the present state-of-the-arts largely either lack of high quality solutions or require excessive amount of time in real-world `Big Data' requirement.

This research aims at affirmatively boosting the modern algorithmic efficiency to approach practical requirements. That is developing a ground-breaking class of algorithms that provide simultaneously both provably good solution qualities and low time and space complexities. Specifically, I target the important yet challenging problems in the three main areas:

Information Diffusion: Analyzing and maximizing the influence in networks and extending results for different variations of the problems.

Community Detection: Finding communities from multiple sources of information.

Security and Privacy: Assessing organization vulnerability under targeted-cyber attacks via social networks.

Rights

© The Author

Is Part Of

VCU University Archives

Is Part Of

VCU Theses and Dissertations

Date of Submission

6-7-2018

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