GPS Spoofing Attack Against UAVs: A Timeseries Dataset Case Study
| dc.contributor.author | Mustapha, Mouzai | |
| dc.contributor.author | Amine, Riahla Mohamed | |
| dc.date.accessioned | 2025-12-08T08:48:09Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | Over the past few years, the world has witnessed a notable surge in the adoption of Unmanned Aerial Vehicles in civil and military applications, including border surveillance, search and rescue, agriculture and delivery. In contrast, this potential growth has been accompanied by the lack of necessary security mechanisms that respond to the threats and vulnerabilities posed by malicious actors. Therefore, in this study we investigate one of the stealthiest attacks that afflict the navigation system of UAVs named GPS Spoofing attack. We overview the different detection techniques existing in literature, and highlight machine learning based approaches dealing with time series data | |
| dc.identifier.isbn | 978-303200551-9 | |
| dc.identifier.uri | https://dspace.univ-boumerdes.dz/handle/123456789/15842 | |
| dc.identifier.uri | https://link.springer.com/chapter/10.1007/978-3-032-00552-6_14 | |
| dc.language.iso | en | |
| dc.publisher | Springer Science and Business Media | |
| dc.relation.ispartofseries | Lecture Notes in Computer Science/vol. 15540; pp. 195 - 208 | |
| dc.relation.ispartofseries | 7th International Conference on Machine Learning for Networking, MLN 2024 | |
| dc.subject | GPS Spoofing attack | |
| dc.subject | Machine learning | |
| dc.subject | Unmanned aerial vehicles | |
| dc.title | GPS Spoofing Attack Against UAVs: A Timeseries Dataset Case Study | |
| dc.type | Article |
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