Drive me not: GPS spoofing detection via cellular network (architectures, models, and experiments)

Gabriele Oligeri, Savio Sciancalepore, Omar Adel Ibrahim, Roberto Di Pietro

Research output: Chapter in Book/Report/Conference proceedingConference contribution

36 Scopus citations

Abstract

The Global Positioning System (GPS) has been proved to be exposed to several cybersecurity attacks, due to its intrinsic insecure design. GPS spoofing is one of the most easiest, cheap, and dreadful attacks that can be delivered: fake GPS signals can be sent to a target device and make it moving according to a pre-computed path. Although some proposals exist to discriminate between legitimate and rogue GPS signals, those solutions are still difficult to deploy, since they resort to special hardware capable of identifying physical properties of original GPS signals. In this paper, we propose a brand new approach, exploiting the broadcast signals transmitted by the mobile cellular network infrastructure to validate the position received by the GPS infrastructure. In detail, we provide several contributions: (i) the architecture of our solution; (ii) the analytic models related to the GSM infrastructure, including the number of in-range base stations, the distance to the base stations, and the received signal strength; and, (iii) the results achieved via an extensive measurement campaign, carried out by first collecting GPS signals while driving for more than 158 Km, and then using these data to build an experimental model for the evaluation of the performance of our technique in the detection of a wide number of emulated spoofing attacks. Finally, we also tested our solution against a real GPS spoofing attack. We proved it being able to guarantee 0% false positive and 100% detection with an almost negligible delay-all the system parameters being finely tunable, allowing for a wide range of possible trade-offs.
Original languageEnglish (US)
Title of host publicationWiSec 2019 - Proceedings of the 2019 Conference on Security and Privacy in Wireless and Mobile Networks
PublisherAssociation for Computing Machinery, Incacmhelp@acm.org
Pages12-22
Number of pages11
ISBN (Print)9781450367264
DOIs
StatePublished - May 15 2019
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-09-20

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