Real-time Stealth GPS Spoofing Attacks On Consumer Drones
| dc.contributor.advisor | Dong, Yingfei | |
| dc.contributor.author | Banh, Nguyen | |
| dc.contributor.department | Electrical Engineering | |
| dc.date.accessioned | 2022-07-05T19:58:33Z | |
| dc.date.available | 2022-07-05T19:58:33Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | While vulnerabilities in unmanned drone software have been extensively explored, hardware vulnerabilities have received less attentions. In this project, we focus on the weaknesses of civilian GPS receivers on consumer drones and investigate their impacts on these drones. By exploiting the vulnerabilities of drone control software and civilian GPS systems, we develop a novel framework for GPS spoofing attacks on consumer drones. In this thesis, we will first introduce the details of drone control systems and the GPS system. We will then present the design of the proposed framework and the evaluation of the framework. Different from most existing GPS spoofing attacks which mostly use brute force approaches, we develop a real-time spoofing framework that utilizes live satellite ephemeral data to significantly improve the success rate of spoofing attacks and achieve better stealth spoofing effects. We also modified the open source bladeGPS software to generate and send real-time GPS signals. While the tests in our laboratory have shown that the proposed framework is very effective, it is still very challenging to evaluate it in practical testing, due to the limitations of the common off-shelf equipment available for the tests, the environment circumstances, and other factors beyond our control, such as wind velocity and cloud cover. We have conducted a number of experiments to better understand the practical challenges, as well as to show that the capabilities of the proposed framework. Furthermore, we present our results and findings and discuss future research issues. | |
| dc.description.degree | M.S. | |
| dc.identifier.uri | https://hdl.handle.net/10125/102230 | |
| dc.language | eng | |
| dc.publisher | University of Hawaii at Manoa | |
| dc.subject | Electrical engineering | |
| dc.title | Real-time Stealth GPS Spoofing Attacks On Consumer Drones | |
| dc.type | Thesis | |
| dc.type.dcmi | Text | |
| local.identifier.alturi | http://dissertations.umi.com/hawii:11430 |
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