Drive me not: GPS spoofing detection via cellular network

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

doi:10.1145/3317549.3319719

Cited by 36 publications

(31 citation statements)

References 16 publications

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“…GPS spoofing attacks can also be detected by comparing the GPS position information with alternative sources of location. Examples of out-of-band means for positioning that can be combined with GPS are visual sensors, Inertial Measurement Units (IMUs), WiFi, altimeters, enhanced long-range navigation (E-LORAN), and cellular-based location [2,42]. Our proposed approach falls into this category.…”

Section: Defenses Against Gps Attacksmentioning

confidence: 99%

DeepSIM: GPS Spoofing Detection on UAVs using Satellite Imagery Matching

Xue

Niu

Hong

et al. 2020

Annual Computer Security Applications Conference

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Section: Defenses Against Gps Attacksmentioning

confidence: 99%

DeepSIM: GPS Spoofing Detection on UAVs using Satellite Imagery Matching

Xue

Niu

Hong

et al. 2020

Annual Computer Security Applications Conference

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“…Several works have suggested disrupting device-to-device communications by resorting to jammers. For instance, by preventing both positioning and navigation with the disruption of the GPS link [40]. Furthermore, a jammer can prevent the usage of the Industrial Scientific and Medical (ISM) band for data communication, or inhibit the Wi-Fi communications adopted for both telemetry and wireless video transmission [41].…”

Section: Defeating Drones With Jammingmentioning

confidence: 99%

Leveraging Jamming to Help Drones Complete Their Mission

2020

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We propose JAM-ME, an autonomous jamming-assisted navigation system that allows a drone to accomplish its mission even in the presence of an anti-drone jamming protection system. In this contribution, we review the current state-of-the-art highlighting how current solutions to respond to drones are completely ineffective against JAM-ME. In particular, we introduce our solution and its theoretical framework, and later we relax a few constraints of the baseline model (adding wind drift, and allowing the target to be randomly placed within the jammed area). Moreover, we run extensive simulations that do support our findings: even under the combined action of jamming and wind drift, the drone can reach a target randomly deployed in the jamming area-any other drone, under the same conditions, would have simply failed. As per the overhead, under very conservative assumptions, JAM-ME experiences an average overhead of 70%; however, note that such overhead can be reduced by at least a tenfold factor in practical settings-discussed in the paper. Finally, we highlight the intrinsic limitations of our solution, potential countermeasures, and new jamming strategies that can pave the way to further research.

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“…There are lots of existing countermeasures. Oligeri et al proposed a brand new approach, validating the position of GPS by contrasting with the position obtained by the mobile cellular network infrastructure in [10]. Such a method could work very well in cellphones and other devices with the cellular network.…”

Section: Countermeasuresmentioning

confidence: 99%

GPS Spoofing Detection via SNR

Diao

Xin

Yang

et al. 2020

Proceedings of the 1st ACM International Workshop on Security and Safety for Intelligent Cyber-Physical Systems

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Nowadays, the use of GPS has penetrated everyone's daily life, so the safety of GPS signals has threatened all of us. Since the portable GPS spoof was proposed at the Black Hat Conference, the cost and threshold of GPS spoofing have also been getting lower and lower. However, many strategies for anti-GPS spoofing may need to add new hardware equipment or require powerful computing power. We aim to use the smallest possible cost to complete the purpose of GPS spoofing detection. In this article, we have designed There are many different detection schemes, and their detection delay and accuracy are different. To prove their feasibility, we did a real experiment. We evaluated the performance of the system based on the experiment, and the results show that the system accuracy is as high as 98%. CCS CONCEPTS • Security and privacy → Hardware attacks and countermeasures; • Information systems → Global positioning systems.

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Drive me not: GPS spoofing detection via cellular network

Cited by 36 publications

References 16 publications

DeepSIM: GPS Spoofing Detection on UAVs using Satellite Imagery Matching

DeepSIM: GPS Spoofing Detection on UAVs using Satellite Imagery Matching

Leveraging Jamming to Help Drones Complete Their Mission

GPS Spoofing Detection via SNR

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