Defending Against GPS Spoofing by Analyzing Visual Cues

Massive GPS navigation services are used by billions of people in their daily lives. GPS spoofing is quite a challenging problem nowadays. Existing Anti-GPS spoofing systems primarily focus on expensive equipment and complicated algorithms, which are not practical and deployable for most of the users. In this thesis, we explore the feasibility of a simple text-based system design for Anti-GPS spoofing. The goal is to use the lower cost and make the system more effective and robust for general spoofing attack detection. Our key idea is to only use the textual information from the physical world and build a real-time system to detect GPS spoofing. To demonstrate the feasibility, we first design image processing modules to collect sufficient textual information in panoramic images. Then, we simulate real-world spoofing attacks from two cities to build our training and testing datasets. We utilize LSTM to build a binary classifier which is the key for our Anti-GPS spoofing system. Finally, we evaluate the system performance by simulating driving tests. We prove that our system can achieve more than 98% detection accuracy when the ratio of attacked points in a driving route is more than 50%. Our system has a promising performance for general spoofing attack strategies and it proves the feasibility of using textual information for the spoofing attack detection.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Computer Science and Applications

Department dc:contributor.department

Computer Science

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2020

Author dc:creator

• Xu, Chao

Chair dc:contributor.committeechair

• Wang, Gang Alan

Committee members dc:contributor.committeemember

• Viswanath, Bimal
• Yao, Danfeng (Daphne)

• GPS Spoofing
• Location Verification
• System Design

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:25813

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/98525