Master of Science, University of Toledo, 2015, Engineering (Computer Science)

Unmanned systems or remotely piloted vehicles can easily accomplish tasks where human lives would be at risk. These systems are being deployed in areas which would be time-consuming, expensive and inconclusive if done by human intervention. Air, ground and underwater vehicles are three major classes of unmanned systems based on their operational environment. Clearly, in terms of causing damage, unmanned aerial vehicles (UAVs) are most efficient and have been known to change the course of several recent wars. If security of these systems is compromised, it will pose a serious threat to human lives as well as the nation. Therefore, it is important to analyze various possible attacks that can be attempted on these systems. Federal Aviation Administration (FAA) has limited the use of UAVs to 400 feet or below in the US National Airspace (NAS), primarily, due to the threat to the general population. This makes real world testing difficult in an academic setup. The best solution to this problem is to have a simulation based environment where different operational scenarios, related cyber-attacks, and their impacts on UAVs can be easily studied. Software based simulators are very economical to test different features of a UAV in terms of various defense mechanisms against cyber-attacks. In this thesis, we enhance UAVSim, a simulation test-bed for UAV Network cyber-security analysis, to include the Global Navigation Satellite System (GNSS), or more specifically, the Global Positioning System (GPS). The testbed allows users to perform security experiments by adjusting different parameters of the satellites and UAVs. It also allows implementation of different attacks in attack hosts. In addition, each UAV host works on well-defined mobility framework, radio propagation models, etc., resembling real-world operational scenarios.

Committee: Weiqing Sun Dr. (Advisor); Mansoor Alam Dr. (Committee Co-Chair); Hong Wang Dr. (Committee Member) Subjects: Computer Engineering