Degree Type

Thesis

Date of Award

2019

Degree Name

Master of Engineering

Department

Electrical and Computer Engineering

Major

Information Assurance

First Advisor

Jennifer L. Newman

Abstract

There are billions of people that use social media as a way to share information and communicate with other users around the world and these social media sites provide easy platforms for sharing images. Digital images can be used to hide messages which may contain incriminating evidence or malware. This project focused on how images with hidden messages, called steganographic (stego) images, can be shared on social media and how to detect the presence of such images. Two case studies were performed with the goal of finding a way to both share images on Facebook and Twitter that contain hidden messages and also to detect the presence of such images. This study found that it is possible to share such images on Facebook and Twitter when following a very specific method. Additionally, Quantization Matrices can be used to gather information about said images which may include whether or not the image in question is a stego image.

Copyright Owner

Lindsey Kathryn Trotter

Language

en

File Format

application/pdf

File Size

62 pages

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