DETECTOR: Automatic detection system for terrorist attack trajectories

Isaias Hoyos; Bruno Esposito; Miguel Nunez-del-Prado

doi:10.1007/978-3-030-11680-4_17

DETECTOR: Automatic detection system for terrorist attack trajectories

Isaias Hoyos, Bruno Esposito, Miguel Nunez-del-Prado

Universidad del Pacífico

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

2 Citas (Scopus)

Resumen

To guarantee national security against terrorist attacks or organized crime, states must implement homeland security solutions based on ubiquitous systems to know in advance the number of suspects involved in an attack. This work proposes a method, which combines popular trajectory similarity metrics to estimate the number of attackers participating in a malicious act through the analysis of the trajectories described by the attacker’s cell phone connection to antennas (i.e. Call Detail Records). Therefore, measuring trajectory similarity in CDRs generates different challenges compared to those similar metrics applied over GPS and video datasets.

Idioma original	Inglés
Título de la publicación alojada	Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings
Editores	Hugo Alatrista-Salas, Juan Antonio Lossio-Ventura, Denisse Muñante
Lugar de publicación	Cham
Páginas	160-173
Número de páginas	14
ISBN (versión digital)	9783030116798
DOI	https://doi.org/10.1007/978-3-030-11680-4_17
Estado	Publicada - 1 ene. 2019
Evento	Communications in Computer and Information Science - Duración: 1 ene. 2019 → …

Serie de la publicación

Nombre	Communications in Computer and Information Science
Volumen	898
ISSN (versión impresa)	1865-0929

Conferencia

Conferencia	Communications in Computer and Information Science
Período	1/01/19 → …

Nota bibliográfica

Publisher Copyright:
© 2019, Springer Nature Switzerland AG.

Palabras clave

Similarity
Terrorist
Trajectory

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

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10.1007/978-3-030-11680-4_17

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Hoyos, I., Esposito, B., & Nunez-del-Prado, M. (2019). DETECTOR: Automatic detection system for terrorist attack trajectories. En H. Alatrista-Salas, J. A. Lossio-Ventura, & D. Muñante (Eds.), Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings (pp. 160-173). (Communications in Computer and Information Science; Vol. 898).. https://doi.org/10.1007/978-3-030-11680-4_17

Hoyos, Isaias ; Esposito, Bruno ; Nunez-del-Prado, Miguel. / DETECTOR: Automatic detection system for terrorist attack trajectories. Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings. editor / Hugo Alatrista-Salas ; Juan Antonio Lossio-Ventura ; Denisse Muñante. Cham, 2019. pp. 160-173 (Communications in Computer and Information Science).

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Hoyos, I, Esposito, B & Nunez-del-Prado, M 2019, DETECTOR: Automatic detection system for terrorist attack trajectories. En H Alatrista-Salas, JA Lossio-Ventura & D Muñante (eds.), Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings. Communications in Computer and Information Science, vol. 898, Cham, pp. 160-173, Communications in Computer and Information Science, 1/01/19. https://doi.org/10.1007/978-3-030-11680-4_17

DETECTOR: Automatic detection system for terrorist attack trajectories. / Hoyos, Isaias; Esposito, Bruno; Nunez-del-Prado, Miguel.
Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings. ed. / Hugo Alatrista-Salas; Juan Antonio Lossio-Ventura; Denisse Muñante. Cham, 2019. p. 160-173 (Communications in Computer and Information Science; Vol. 898).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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Hoyos I, Esposito B, Nunez-del-Prado M. DETECTOR: Automatic detection system for terrorist attack trajectories. En Alatrista-Salas H, Lossio-Ventura JA, Muñante D, editores, Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings. Cham. 2019. p. 160-173. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-11680-4_17

DETECTOR: Automatic detection system for terrorist attack trajectories

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Serie de la publicación

Conferencia

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Palabras clave

ODS de las Naciones Unidas

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