Terrorist network monitoring with identifying code

Arunabha Sen, Victoria Horan Goliber, Chenyang Zhou, Kaustav Basu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

On multiple incidences of terrorist attacks in recent times across Europe, it has been observed that the perpetrators of the attack were in the suspect databases of the law enforcement authorities, but weren’t under active surveillance at the time of the attack due to resource limitations on the part of the authorities. As the suspect databases in various European countries are very large, and it takes significant amount of technical and human resources to monitor a suspect in the database, monitoring all the suspects in the database may be an impossible task. In this paper, we propose a scheme utilizing Identifying Codes that will significantly reduce the resource requirement of law enforcement authorities, and will have the capability of uniquely identifying a suspect in case the suspect becomes active in planning a terrorist attack. The scheme relies on the assumption that, when an individual becomes active in planning a terrorist attack, his/her friends/associates will have some inkling of the individuals plan. Accordingly, even if the individual is not under active surveillance by the authorities, but the individual’s friends/associates are, the individual planning the attack can be uniquely identified. We applied our technique on two terrorist networks, one involved in an attack in Paris and the other involved in the 9/11 attack. We show that, in the Paris network, if 5 of the 10 individuals were monitored, the attackers most likely would have been exposed. If only 15 out of the 37 individuals involved in the 9/11 attack were under surveillance, specific individuals involved in the planning of the 9/11 attack would have been exposed.

Original languageEnglish (US)
Title of host publicationSocial, Cultural, and Behavioral Modeling - 11th International Conference, SBP-BRiMS 2018, Proceedings
EditorsHalil Bisgin, Robert Thomson, Ayaz Hyder, Christopher Dancy
PublisherSpringer Verlag
Pages329-339
Number of pages11
ISBN (Print)9783319933719
DOIs
StatePublished - Jan 1 2018
Event11th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction conference and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2018 - Washington, United States
Duration: Jul 10 2018Jul 13 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10899 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other11th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction conference and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2018
CountryUnited States
CityWashington
Period7/10/187/13/18

Keywords

  • Approximation algorithm
  • Computational complexity
  • Identification code
  • Terrorist network

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Sen, A., Goliber, V. H., Zhou, C., & Basu, K. (2018). Terrorist network monitoring with identifying code. In H. Bisgin, R. Thomson, A. Hyder, & C. Dancy (Eds.), Social, Cultural, and Behavioral Modeling - 11th International Conference, SBP-BRiMS 2018, Proceedings (pp. 329-339). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10899 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-93372-6_36