Graduation Semester and Year
2015
Language
English
Document Type
Thesis
Degree Name
Master of Science in Electrical Engineering
Department
Electrical Engineering
First Advisor
Frank Lewis
Abstract
The Federal Aviation Administration (FAA) estimates that by the year 2020, the United States will have over 30,000 drones. Today, the fields of utilization of drones, also known as Unmanned Aerial Vehicles (UAV) are unlimited. UAVs can be used in hazardous military missions, since they exclude the risk factors involved in manned vehicles. The numerous sensors on board gather data related to the desired flight plan. This exposes UAVs to various vulnerabilities since they carry enormous information and raises safety issues and privacy concerns. Absence of manual control by a human operator over the UAV results in fraudulent information being fed and navigated to a different location by the attacker. On gaining control of the system, sensitive data can be accessed and misused. The objective of this research is to study, develop and implement various security, threat assessment and response systems on autonomous systems.
Disciplines
Electrical and Computer Engineering | Engineering
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Veeranna Gowda, Chaitanya Rani, "System Security, Threat Detection And Prevention Measures Of Autonomous Systems" (2015). Electrical Engineering Theses. 287.
https://mavmatrix.uta.edu/electricaleng_theses/287
Comments
Degree granted by The University of Texas at Arlington