Ciberseguridad Satelital: Machine Learning para preservar integridad de señales GPS en aeronaves de la FAC
| dc.contributor.author | Cruz, Sergio Baudin | |
| dc.coverage.temporal | 2020-2025 | |
| dc.date.accessioned | 2026-04-30T11:36:44Z | |
| dc.date.available | 2026-04-30T11:36:44Z | |
| dc.date.issued | 2025-03-15 | |
| dc.date.submitted | 2025-07-15 | |
| dc.identifier.citation | Aceves-Fernandez, M. A. (Ed.). (2023). Machine Learning and Data Mining. IntechOpen. Adamczyk, M. (2024, mayo 7). Current state of cybersecurity threat landscape in space sector [Video]. YouTube. https://www.youtube.com/watch?v=dysNoQ4ACAg Aerospace Corporation. (2022a). Countermeasures | SPARTA. https://sparta.aerospace.org/countermeasures/SPARTA Aerospace Corporation. (2022b). Defense-in-Depth for Space Systems. https://sparta.aerospace.org/related-work/did-space Aerospace Corporation. (2022c). Erroneous Input, Technique EX-0013.02 | SPARTA. https://sparta.aerospace.org/technique/EX-0013/02/ Aerospace Corporation. (2022d). Execution, Tactic ST0004 | SPARTA. https://sparta.aerospace.org/tactic/ST0004 Aerospace Corporation. (2022e). Position, Navigation, and Timing (PNT) Jamming, Technique EX-0016.03 | SPARTA. https://sparta.aerospace.org/technique/EX-0016/03/ Aerospace Corporation. (2022f). Position, Navigation, and Timing (PNT) Spoofing, Technique EX-0014.04 | SPARTA. https://sparta.aerospace.org/technique/EX-0014/04/ Agyemang, E. F. (2024). Anomaly detection using unsupervised machine learning algorithms: A simulation study. Scientific African, 26, e02386. https://doi.org/10.1016/j.sciaf.2024.e02386 Amr, T. (2020). Hands-on machine learning with scikit-learn and scientific Python toolkits: A practical guide to implementing supervised and unsupervised machine learning algorithms in Python. Packt. Bailey, B. (2021). Cybersecurity Protections for Spacecraft: A Threat Based Approach. AEROSPACE REPORT NO. TOR-2021-01333-REV A. Bailey, B. (2025, mayo). Needed advancement for research and development in space cybersecurity. The Aerospace Corporation. https://aerospace.org/sites/default/files/2025-05/AdvancementInSpaceCybersecurity_Bailey_20250506.pdf Barua, T., Hiran, K. K., Jain, R. K., & Doshi, R. (2024). Machine Learning with Python. De Gruyter. https://doi.org/10.1515/9783110697186 Calian Group. (2025). GNSS Constellations, Radio Frequencies and Signals—AT | Calian. Advanced Technologies. https://www.calian.com/advanced-technologies/gnss/information-support/gnss-constellations-radio-frequencies-and-signals/ Delgado, T., & Carmona Tapia, C. (2024, mayo 7). The security-by-design approach when building a new LEO constellation. [Video]. YouTube. https://www.youtube.com/watch?v=YIL1V2WAzf0 De Luca, G. (2024, marzo 18). Haversine Formula | Baeldung on Computer Science. https://www.baeldung.com/cs/haversine-formula Ear, E., Remy, J. L. C., Feffer, A., & Xu, S. (2023). Characterizing Cyber Attacks against Space Systems with Missing Data: Framework and Case Study (No. arXiv:2309.04878). arXiv. https://doi.org/10.48550/arXiv.2309.04878 Edgar, T. W., & Manz, D. O. (2017). Research methods for cyber security. Syngress, an imprint of Elsevier. Feldman, M., & Taylor, H. (2025). Space Piracy: Preparing for a Criminal Crisis in Orbit. John Wiley and Sons. Garcia, D. (2017). AFSCN Remote Tracking Station. https://www.gps.gov/multimedia/images/GPS-control-segment-map.pdf Hamill-Stewart, J. (2024, mayo 7). Threats against satellite ground infrastructure: Retrospective analysis of attacks. [Video]. YouTube. https://www.youtube.com/watch?v=ATFlNgy-XoA Hamill-Stewart, J., & Rashid, A. (2024). Threats Against Satellite Ground Infrastructure: A retrospective analysis of sophisticated attacks. Proceedings 2024 Workshop on Security of Space and Satellite Systems. Workshop on Security of Space and Satellite Systems, San Diego, CA, USA. https://doi.org/10.14722/spacesec.2024.23087 Huang, H., Wang, P., Pei, J., Wang, J., Alexanian, S., & Niyato, D. (2025). Deep Learning Advancements in Anomaly Detection: A Comprehensive Survey (No. arXiv:2503.13195). arXiv. https://doi.org/10.48550/arXiv.2503.13195 Johanna Niecknig, Wendel Lohmer, Max Gebhardt, Stefanie Grundner, Manuel Hoffmann, André Penzien, Steffen Kuntz, Miriam Goellner, Tarsicio López Delgado, Frank Keck, Matthias Berger, & Sascha Fankhänel. (2023). Technical Guideline BSI TR-03184 Information Security for Space Systems—Part 1: Space segment. 1.0. Joshi, S., Bairwa, A. K., Nandal, A., Radenkovic, M., & Avsar, C. (Eds.). (2022). Cyber Warfare, Security and Space Research: First International Conference, SpacSec 2021, Jaipur, India, December 9–10, 2021, Revised Selected Papers (Vol. 1599). Springer International Publishing. https://doi.org/10.1007/978-3-031-15784-4 Kavallieratos, G., & Katsikas, S. (2023). An exploratory analysis of the last frontier: A systematic literature review of cybersecurity in space. International Journal of Critical Infrastructure Protection, 43, 100640. https://doi.org/10.1016/j.ijcip.2023.100640 McCarthy, J., Li-Baboud, Y.-S., Brule, J., & Meldorf, K. (2023). Foundational PNT profile: Applying the cybersecurity framework for the responsible use of positioning, navigation, and timing (PNT) services (No. NIST IR 8323r1; p. NIST IR 8323r1). National Institute of Standards and Technology (U.S.). https://doi.org/10.6028/NIST.IR.8323r1 Oakley, J. G. (2020). Cybersecurity for Space: Protecting the Final Frontier. Apress. https://doi.org/10.1007/978-1-4842-5732-6 Patel, A. A. (2019). Hands-On unsupervised learning using Python: How to build applied machine learning solutions from unlabeled data (First edition, second release). O’Reilly. Periyasami, K., Katina, P. F., & Ramasamy, R. (Eds.). (2024). Cyber space and outer space security. River Publishers. https://doi.org/10.1201/9781003558118 Poirier, C. (2024, mayo 7). The dynamics of cyber conflicts on space systems in the war in Ukraine. [Video]. YouTube. https://www.youtube.com/watch?v=RS_WYP-MuNo Raspberry Pi Ltd. (2020). Raspberry Pi 4 Model B. Raspberry Pi. https://www.raspberrypi.com/products/raspberry-pi-4-model-b/ Rushanan, J. J., & Gillis, J. T. (2025). Cryptography and satellite navigation. Artech House. Salerno, S. (2025). Tiny Machine Learning Quickstart: Machine Learning for Arduino Microcontrollers. Apress. https://doi.org/10.1007/979-8-8688-1294-1 Sarang, P. (2023). Thinking Data Science: A Data Science Practitioner’s Guide. Springer International Publishing. https://doi.org/10.1007/978-3-031-02363-7 Scholl, M., & Suloway, T. (2023). Introduction to cybersecurity for commercial satellite operations (No. NIST IR 8270; p. NIST IR 8270). National Institute of Standards and Technology (U.S.). https://doi.org/10.6028/NIST.IR.8270 Shahzad, S., Deane, F., Joiner, K. F., Qiao, L., & Suprun, E. (2024). Cyber Resilience in Space Infrastructure: Strategies for Protecting Critical Space Assets. SSRN. https://doi.org/10.2139/ssrn.5076427 Stanford University. (2023, octubre). GNSS Interference Detection using ADS-B. Stanford GPS Lab. https://waas-nas.stanford.edu/#/heatmapSpof/2024_10_23/ Tang, A. C. B. (2021). A Review on Cybersecurity Vulnerabilities for Urban Air Mobility. https://doi.org/10.2514/6.2021-0773 Wade, N. M. (2019). Cyber 1: The cyberspace operations & electronic warfare SMARTbook : multi-domain guide to offensive/defensive CEMA and CO (First edition). Lightning Press. Winn, J. M., & Diethe, T. (with Bishop, C. M., Guiver, J., & Zaykov, Y.). (2024). Model-based machine learning (First edition). CRC Press. | es_ES |
| dc.identifier.uri | https://hdl.handle.net/20.500.14205/11865 | |
| dc.description.abstract | El estudio aborda temas de ciberseguridad satelital en el uso del GPS por parte de la Fuerza Aeroespacial Colombiana, enfocándose en el segmento de usuario del sistema satelital, mediante la aplicación de metodologías observacional y experimental para identificar vulnerabilidades, amenazas y posibles ataques, destacándose el spoofing como un ataque crítico a la integridad de los datos GPS. Como respuesta, se diseñó un modelo de aprendizaje automático basado en Random Forest, entrenado con datos reales y simulados, que permite detectar señales anómalas en tiempo real a bordo de aeronaves. El modelo fue implementado en una Raspberry Pi, validado en simulaciones y pruebas de campo, con la finalidad de mejorar la resiliencia y seguridad operacional frente a ciberataques al sistema satelital GPS. | es_ES |
| dc.description.abstract | The target of this study is satellite cybersecurity in the GPS uses by the Colombian Aerospace Force, focusing on the user segment of the satellite system. It applies observational and experimental methodologies to identify vulnerabilities, threats, and potential attacks, highlighting spoofing as a critical threat to the integrity of GPS data. As a response, a machine learning model based on Random Forest was designed, trained with real and simulated data, enabling real-time detection of anomalous signals aboard aircraft. The model was implemented on a Raspberry Pi, validated through simulations and field tests, with the aim of enhancing resilience and operational safety against cyberattacks targeting the Global Positioning System. | es_ES |
| dc.description.tableofcontents | Introducción 7 Metodología 9 Amenazas invisibles: vulnerabilidades y ciber-riesgos en la Infraestructura Satelital 11 Puntos críticos en el sistema satelital: vulnerabilidades conocidas en hardware, software y transmisión 14 Vulnerabilidades en hardware 14 Vulnerabilidades en software 16 Vulnerabilidades en transmisión 17 Consecuencias críticas: ciber-riesgos asociados a la integridad de datos satelitales 19 Vectores de ataque en la constelación GPS: ciberamenazas del sistema 19 Segmento terrestre 19 Segmento de usuario 20 Actores y ataques materializados relevantes 21 Defensas cibernéticas en el espacio: estrategias de mitigación para la ciberseguridad satelital 23 Modelos de ciberseguridad para integridad de datos: arquitecturas y frameworks de protección en sistemas satelitales 24 Tácticas, técnicas y contramedidas del framework SPARTA para integridad de datos 25 Fortificando el segmento de usuario: contramedidas para salvaguardar la integridad de la señal GPS 31 Inteligencia artificial aplicada en ciberseguridad: modelo de ML para verificación de integridad de datos GPS 33 Fundamentos del modelo: algoritmos y técnicas conocidas de Machine Learning 36 Entrenamiento y validación del modelo: uso de datos simulados y reales para la precisión 39 Validación y evaluación: como se podría integrar el modelo en una operación de la FAC 45 Conclusiones 51 Referencias 57 | es_ES |
| dc.format.extent | 61 páginas | |
| dc.format.mimetype | application/pdf | es_ES |
| dc.language.iso | spa | es_ES |
| dc.rights.uri | http://creativecommons.org/publicdomain/zero/1.0/ | * |
| dc.title | Ciberseguridad Satelital: Machine Learning para preservar integridad de señales GPS en aeronaves de la FAC | es_ES |
| dc.title.alternative | Satellite Cybersecurity: Machine Learning to preserve GPS integrity signals of Colombian Air Space Force aircrafts | es_ES |
| dcterms.bibliographicCitation | Aceves-Fernandez, M. A. (Ed.). (2023). Machine Learning and Data Mining. IntechOpen. | es_ES |
| dcterms.bibliographicCitation | Adamczyk, M. (2024, mayo 7). Current state of cybersecurity threat landscape in space sector [Video]. YouTube. https://www.youtube.com/watch?v=dysNoQ4ACAg | es_ES |
| dcterms.bibliographicCitation | Aerospace Corporation. (2022a). Countermeasures | SPARTA. https://sparta.aerospace.org/countermeasures/SPARTA | es_ES |
| dcterms.bibliographicCitation | Aerospace Corporation. (2022b). Defense-in-Depth for Space Systems. https://sparta.aerospace.org/related-work/did-space | es_ES |
| dcterms.bibliographicCitation | Aerospace Corporation. (2022c). Erroneous Input, Technique EX-0013.02 | SPARTA. https://sparta.aerospace.org/technique/EX-0013/02/ | es_ES |
| dcterms.bibliographicCitation | Aerospace Corporation. (2022d). Execution, Tactic ST0004 | SPARTA. https://sparta.aerospace.org/tactic/ST0004 | es_ES |
| dcterms.bibliographicCitation | Aerospace Corporation. (2022e). Position, Navigation, and Timing (PNT) Jamming, Technique EX-0016.03 | SPARTA. https://sparta.aerospace.org/technique/EX-0016/03/ | es_ES |
| dcterms.bibliographicCitation | Aerospace Corporation. (2022f). Position, Navigation, and Timing (PNT) Spoofing, Technique EX-0014.04 | SPARTA. https://sparta.aerospace.org/technique/EX-0014/04/ | es_ES |
| dcterms.bibliographicCitation | Agyemang, E. F. (2024). Anomaly detection using unsupervised machine learning algorithms: A simulation study. Scientific African, 26, e02386. https://doi.org/10.1016/j.sciaf.2024.e02386 | es_ES |
| dcterms.bibliographicCitation | Amr, T. (2020). Hands-on machine learning with scikit-learn and scientific Python toolkits: A practical guide to implementing supervised and unsupervised machine learning algorithms in Python. Packt. | es_ES |
| dcterms.bibliographicCitation | Bailey, B. (2021). Cybersecurity Protections for Spacecraft: A Threat Based Approach. AEROSPACE REPORT NO. TOR-2021-01333-REV A. | es_ES |
| dcterms.bibliographicCitation | Bailey, B. (2025, mayo). Needed advancement for research and development in space cybersecurity. The Aerospace Corporation. https://aerospace.org/sites/default/files/2025-05/AdvancementInSpaceCybersecurity_Bailey_20250506.pdf | es_ES |
| dcterms.bibliographicCitation | Barua, T., Hiran, K. K., Jain, R. K., & Doshi, R. (2024). Machine Learning with Python. De Gruyter. https://doi.org/10.1515/9783110697186 | es_ES |
| dcterms.bibliographicCitation | Calian Group. (2025). GNSS Constellations, Radio Frequencies and Signals—AT | Calian. Advanced Technologies. https://www.calian.com/advanced-technologies/gnss/information-support/gnss-constellations-radio-frequencies-and-signals/ | es_ES |
| dcterms.bibliographicCitation | Delgado, T., & Carmona Tapia, C. (2024, mayo 7). The security-by-design approach when building a new LEO constellation. [Video]. YouTube. https://www.youtube.com/watch?v=YIL1V2WAzf0 | es_ES |
| dcterms.bibliographicCitation | De Luca, G. (2024, marzo 18). Haversine Formula | Baeldung on Computer Science. https://www.baeldung.com/cs/haversine-formula | es_ES |
| dcterms.bibliographicCitation | Ear, E., Remy, J. L. C., Feffer, A., & Xu, S. (2023). Characterizing Cyber Attacks against Space Systems with Missing Data: Framework and Case Study (No. arXiv:2309.04878). arXiv. https://doi.org/10.48550/arXiv.2309.04878 | es_ES |
| dcterms.bibliographicCitation | Edgar, T. W., & Manz, D. O. (2017). Research methods for cyber security. Syngress, an imprint of Elsevier. | es_ES |
| dcterms.bibliographicCitation | Feldman, M., & Taylor, H. (2025). Space Piracy: Preparing for a Criminal Crisis in Orbit. John Wiley and Sons. | es_ES |
| dcterms.bibliographicCitation | Garcia, D. (2017). AFSCN Remote Tracking Station. https://www.gps.gov/multimedia/images/GPS-control-segment-map.pdf | es_ES |
| dcterms.bibliographicCitation | Hamill-Stewart, J. (2024, mayo 7). Threats against satellite ground infrastructure: Retrospective analysis of attacks. [Video]. YouTube. https://www.youtube.com/watch?v=ATFlNgy-XoA | es_ES |
| dcterms.bibliographicCitation | Hamill-Stewart, J., & Rashid, A. (2024). Threats Against Satellite Ground Infrastructure: A retrospective analysis of sophisticated attacks. Proceedings 2024 Workshop on Security of Space and Satellite Systems. Workshop on Security of Space and Satellite Systems, San Diego, CA, USA. https://doi.org/10.14722/spacesec.2024.23087 | es_ES |
| dcterms.bibliographicCitation | Huang, H., Wang, P., Pei, J., Wang, J., Alexanian, S., & Niyato, D. (2025). Deep Learning Advancements in Anomaly Detection: A Comprehensive Survey (No. arXiv:2503.13195). arXiv. https://doi.org/10.48550/arXiv.2503.13195 | es_ES |
| dcterms.bibliographicCitation | Johanna Niecknig, Wendel Lohmer, Max Gebhardt, Stefanie Grundner, Manuel Hoffmann, André Penzien, Steffen Kuntz, Miriam Goellner, Tarsicio López Delgado, Frank Keck, Matthias Berger, & Sascha Fankhänel. (2023). Technical Guideline BSI TR-03184 Information Security for Space Systems—Part 1: Space segment. 1.0. | es_ES |
| dcterms.bibliographicCitation | Joshi, S., Bairwa, A. K., Nandal, A., Radenkovic, M., & Avsar, C. (Eds.). (2022). Cyber Warfare, Security and Space Research: First International Conference, SpacSec 2021, Jaipur, India, December 9–10, 2021, Revised Selected Papers (Vol. 1599). Springer International Publishing. https://doi.org/10.1007/978-3-031-15784-4 | es_ES |
| dcterms.bibliographicCitation | Kavallieratos, G., & Katsikas, S. (2023). An exploratory analysis of the last frontier: A systematic literature review of cybersecurity in space. International Journal of Critical Infrastructure Protection, 43, 100640. https://doi.org/10.1016/j.ijcip.2023.100640 | es_ES |
| dcterms.bibliographicCitation | McCarthy, J., Li-Baboud, Y.-S., Brule, J., & Meldorf, K. (2023). Foundational PNT profile: Applying the cybersecurity framework for the responsible use of positioning, navigation, and timing (PNT) services (No. NIST IR 8323r1; p. NIST IR 8323r1). National Institute of Standards and Technology (U.S.). https://doi.org/10.6028/NIST.IR.8323r1 | es_ES |
| dcterms.bibliographicCitation | Oakley, J. G. (2020). Cybersecurity for Space: Protecting the Final Frontier. Apress. https://doi.org/10.1007/978-1-4842-5732-6 | es_ES |
| dcterms.bibliographicCitation | Patel, A. A. (2019). Hands-On unsupervised learning using Python: How to build applied machine learning solutions from unlabeled data (First edition, second release). O’Reilly. | es_ES |
| dcterms.bibliographicCitation | Periyasami, K., Katina, P. F., & Ramasamy, R. (Eds.). (2024). Cyber space and outer space security. River Publishers. https://doi.org/10.1201/9781003558118 | es_ES |
| dcterms.bibliographicCitation | Poirier, C. (2024, mayo 7). The dynamics of cyber conflicts on space systems in the war in Ukraine. [Video]. YouTube. https://www.youtube.com/watch?v=RS_WYP-MuNo | es_ES |
| dcterms.bibliographicCitation | Raspberry Pi Ltd. (2020). Raspberry Pi 4 Model B. Raspberry Pi. https://www.raspberrypi.com/products/raspberry-pi-4-model-b/ | es_ES |
| dcterms.bibliographicCitation | Rushanan, J. J., & Gillis, J. T. (2025). Cryptography and satellite navigation. Artech House. | es_ES |
| dcterms.bibliographicCitation | Salerno, S. (2025). Tiny Machine Learning Quickstart: Machine Learning for Arduino Microcontrollers. Apress. https://doi.org/10.1007/979-8-8688-1294-1 | es_ES |
| dcterms.bibliographicCitation | Sarang, P. (2023). Thinking Data Science: A Data Science Practitioner’s Guide. Springer International Publishing. https://doi.org/10.1007/978-3-031-02363-7 | es_ES |
| dcterms.bibliographicCitation | Scholl, M., & Suloway, T. (2023). Introduction to cybersecurity for commercial satellite operations (No. NIST IR 8270; p. NIST IR 8270). National Institute of Standards and Technology (U.S.). https://doi.org/10.6028/NIST.IR.8270 | es_ES |
| dcterms.bibliographicCitation | Shahzad, S., Deane, F., Joiner, K. F., Qiao, L., & Suprun, E. (2024). Cyber Resilience in Space Infrastructure: Strategies for Protecting Critical Space Assets. SSRN. https://doi.org/10.2139/ssrn.5076427 | es_ES |
| dcterms.bibliographicCitation | Stanford University. (2023, octubre). GNSS Interference Detection using ADS-B. Stanford GPS Lab. https://waas-nas.stanford.edu/#/heatmapSpof/2024_10_23/ | es_ES |
| dcterms.bibliographicCitation | Tang, A. C. B. (2021). A Review on Cybersecurity Vulnerabilities for Urban Air Mobility. https://doi.org/10.2514/6.2021-0773 | es_ES |
| dcterms.bibliographicCitation | Wade, N. M. (2019). Cyber 1: The cyberspace operations & electronic warfare SMARTbook : multi-domain guide to offensive/defensive CEMA and CO (First edition). Lightning Press. | es_ES |
| dcterms.bibliographicCitation | Winn, J. M., & Diethe, T. (with Bishop, C. M., Guiver, J., & Zaykov, Y.). (2024). Model-based machine learning (First edition). CRC Press. | es_ES |
| datacite.rights | http://purl.org/coar/access_right/c_16ec | es_ES |
| oaire.resourcetype | http://purl.org/coar/resource_type/c_2df8fbb1 | es_ES |
| oaire.version | http://purl.org/coar/version/c_b1a7d7d4d402bcce | es_ES |
| dc.audience | Estudiantes | es_ES |
| dc.contributor.tutor | Dr. Giovanni Gómez Rodríguez | |
| dc.identifier.doi | https://doi.org/10.1016/j.sciaf.2024.e02386 | |
| dc.identifier.doi | https://doi.org/10.1515/9783110697186 | |
| dc.identifier.doi | https://doi.org/10.48550/arXiv.2309.04878 | |
| dc.identifier.doi | https://doi.org/10.14722/spacesec.2024.23087 | |
| dc.identifier.doi | https://doi.org/10.48550/arXiv.2503.13195 | |
| dc.identifier.doi | https://doi.org/10.1007/978-3-031-15784-4 | |
| dc.identifier.doi | https://doi.org/10.1016/j.ijcip.2023.100640 | |
| dc.identifier.doi | https://doi.org/10.6028/NIST.IR.8323r1 | |
| dc.identifier.doi | https://doi.org/10.1007/978-1-4842-5732-6 | |
| dc.identifier.doi | https://doi.org/10.1201/9781003558118 | |
| dc.identifier.doi | https://doi.org/10.1007/979-8-8688-1294-1 | |
| dc.identifier.doi | https://doi.org/10.1007/978-3-031-02363-7 | |
| dc.identifier.doi | https://doi.org/10.1007/978-3-031-02363-7 | |
| dc.identifier.doi | https://doi.org/10.6028/NIST.IR.8270 | |
| dc.identifier.doi | https://doi.org/10.2139/ssrn.5076427 | |
| dc.identifier.doi | https://doi.org/10.2514/6.2021-0773 | |
| dc.identifier.instname | Escuela Superior de Guerra "General Rafael Reyes Prieto" | es_ES |
| dc.identifier.reponame | Repositorio ESDEG | es_ES |
| dc.identifier.url | https://www.youtube.com/watch?v=dysNoQ4ACAg | |
| dc.identifier.url | https://sparta.aerospace.org/countermeasures/SPARTA | |
| dc.identifier.url | https://sparta.aerospace.org/related-work/did-space | |
| dc.identifier.url | https://sparta.aerospace.org/technique/EX-0013/02/ | |
| dc.identifier.url | https://sparta.aerospace.org/tactic/ST0004 | |
| dc.identifier.url | https://sparta.aerospace.org/tactic/ST0004 | |
| dc.identifier.url | https://sparta.aerospace.org/technique/EX-0016/03/ | |
| dc.identifier.url | https://aerospace.org/sites/default/files/2025-05/AdvancementInSpaceCybersecurity_Bailey_20250506.pdf | |
| dc.identifier.url | https://www.calian.com/advanced-technologies/gnss/information-support/gnss-constellations-radio-frequencies-and-signals/ | |
| dc.identifier.url | https://www.youtube.com/watch?v=YIL1V2WAzf0 | |
| dc.identifier.url | https://www.baeldung.com/cs/haversine-formula | |
| dc.identifier.url | https://www.gps.gov/multimedia/images/GPS-control-segment-map.pdf | |
| dc.identifier.url | https://www.youtube.com/watch?v=ATFlNgy-XoA | |
| dc.identifier.url | https://www.youtube.com/watch?v=RS_WYP-MuNo | |
| dc.identifier.url | https://waas-nas.stanford.edu/#/heatmapSpof/2024_10_23/ | |
| dc.publisher.place | Bogotá | es_ES |
| dc.publisher.program | Maestría en Ciberseguridad y Ciberdefensa | es_ES |
| dc.relation.citationEdition | 61 | es_ES |
| dc.rights.accessrights | info:eu-repo/semantics/restrictedAccess | es_ES |
| dc.rights.cc | CC0 1.0 Universal | * |
| dc.subject.armarc | UNESCO | |
| dc.subject.keywords | Ciberseguridad satelital | es_ES |
| dc.subject.keywords | GPS | es_ES |
| dc.subject.keywords | Machine Learning | es_ES |
| dc.subject.keywords | Navigation Warfare | es_ES |
| dc.subject.keywords | Spoofing | es_ES |
| dc.subject.keywords | SPARTA | es_ES |
| dc.subject.keywords | Satellite Cybersecurity | es_ES |
| dc.type.driver | info:eu-repo/semantics/article | es_ES |
| dc.type.hasversion | info:eu-repo/semantics/draft | es_ES |
| dc.type.spa | Animación | es_ES |
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