DETECTOR: Automatic detection system for terrorist attack trajectories

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations


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 languageEnglish
Title of host publicationInformation Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings
EditorsHugo Alatrista-Salas, Juan Antonio Lossio-Ventura, Denisse Muñante
Place of PublicationCham
Number of pages14
ISBN (Electronic)9783030116798
StatePublished - 1 Jan 2019
EventCommunications in Computer and Information Science -
Duration: 1 Jan 2019 → …

Publication series

NameCommunications in Computer and Information Science
ISSN (Print)1865-0929


ConferenceCommunications in Computer and Information Science
Period1/01/19 → …

Bibliographical note

Publisher Copyright:
© 2019, Springer Nature Switzerland AG.


  • Similarity
  • Terrorist
  • Trajectory


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