First Order Feature Extraction Of Internet Traffic
MetadataShow full item record
Type of WorkText
DepartmentElectrical and Computer Engineering
ProgramMaster of Science
RightsThis item is made available by Morgan State University for personal, educational, and research purposes in accordance with Title 17 of the U.S. Copyright Law. Other uses may require permission from the copyright owner.
The Internet has made life easier for people by allowing them to connect with individuals across the world. It has created a world that connects typical devices such as computers, routers, and servers. In recent years, the Internet has made its way into our homes for more than streaming movies and doing homework; the Internet has made its way into devices that are not so typical such as: coffee pots, outlets, and thermostats. Because of these phenomena, people are now able to be connected at all times via the Internet and Wi-Fi networks. The interconnectedness of these devices has led to the study of the Internet of Things (IoT), which is the study of the impact of non-typical devices on the Internet and networks. These devices also allow hackers more points of intrusion on a network. They can be used in an initial phase of large scaled coordinated cyber-attacks known as Advanced Persistent Threat (APT) to access network and establish connections. In order to effectively study IoT and APT, there needs to be a new way to track and understand network activity. The research will attempt to determine the capabilities of Principal Component Analysis (PCA) in order to minimize the amount of information necessary to determine abnormalities in internet traffic which will lead to a more effective study of IoT and APT; while, establishing a framework for creating an active Intrusion Detection System.