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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

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.

Original language	English
Title of host publication	Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings
Editors	Hugo Alatrista-Salas, Juan Antonio Lossio-Ventura, Denisse Muñante
Place of Publication	Cham
Pages	160-173
Number of pages	14
ISBN (Electronic)	9783030116798
DOIs	https://doi.org/10.1007/978-3-030-11680-4_17
State	Published - 1 Jan 2019
Event	Communications in Computer and Information Science - Duration: 1 Jan 2019 → …

Publication series

Name	Communications in Computer and Information Science
Volume	898
ISSN (Print)	1865-0929

Conference

Conference	Communications in Computer and Information Science
Period	1/01/19 → …

Bibliographical note

Publisher Copyright:
© 2019, Springer Nature Switzerland AG.

Keywords

Similarity
Terrorist
Trajectory

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

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

Cite this

Hoyos, I., Esposito, B., & Nunez-del-Prado, M. (2019). DETECTOR: Automatic detection system for terrorist attack trajectories. In 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. in 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).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Hoyos I, Esposito B, Nunez-del-Prado M. DETECTOR: Automatic detection system for terrorist attack trajectories. In Alatrista-Salas H, Lossio-Ventura JA, Muñante D, editors, 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

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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