SPREE: Spoofing Resistant GPS Receiver
March 17, 2016 Β· Declared Dead Β· π ACM/IEEE International Conference on Mobile Computing and Networking
"No code URL or promise found in abstract"
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Authors
Aanjhan Ranganathan, Hildur ΓlafsdΓ³ttir, Srdjan Capkun
arXiv ID
1603.05462
Category
cs.CR: Cryptography & Security
Citations
105
Venue
ACM/IEEE International Conference on Mobile Computing and Networking
Last Checked
3 months ago
Abstract
Global Positioning System (GPS) is used ubiquitously in a wide variety of applications ranging from navigation and tracking to modern smart grids and communication networks. However, it has been demonstrated that modern GPS receivers are vulnerable to signal spoofing attacks. For example, today it is possible to change the course of a ship or force a drone to land in an hostile area by simply spoofing GPS signals. Several countermeasures have been proposed in the past to detect GPS spoofing attacks. These countermeasures offer protection only against naive attackers. They are incapable of detecting strong attackers such as those capable of seamlessly taking over a GPS receiver, which is currently receiving legitimate satellite signals, and spoofing them to an arbitrary location. Also, there is no hardware platform that can be used to compare and evaluate the effectiveness of existing countermeasures in real-world scenarios. In this work, we present SPREE, which is, to the best of our knowledge, the first GPS receiver capable of detecting all spoofing attacks described in literature. Our novel spoofing detection technique called auxiliary peak tracking enables detection of even a strong attacker capable of executing the seamless takeover attack. We implement and evaluate our receiver against three different sets of GPS signal traces and show that SPREE constrains even a strong attacker (capable of seamless takeover attack) from spoofing the receiver to a location not more than 1 km away from its true location. This is a significant improvement over modern GPS receivers that can be spoofed to any arbitrary location. Finally, we release our implementation and datasets to the community for further research and development.
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