@inproceedings{d7635d9a3439426d874c09d2a78583c4,
title = "A generative model for predicting terrorist incidents",
abstract = "A major concern in coalition peace-support operations is the incidence of terrorist activity. In this paper, we propose a generative model for the occurrence of the terrorist incidents, and illustrate that an increase in diversity, as measured by the number of different social groups to which that an individual belongs, is inversely correlated with the likelihood of a terrorist incident in the society. A generative model is one that can predict the likelihood of events in new contexts, as opposed to statistical models which are used to predict the future incidents based on the history of the incidents in an existing context. Generative models can be useful in planning for persistent Information Surveillance and Reconnaissance (ISR) since they allow an estimation of regions in the theater of operation where terrorist incidents may arise, and thus can be used to better allocate the assignment and deployment of ISR assets. In this paper, we present a taxonomy of terrorist incidents, identify factors related to occurrence of terrorist incidents, and provide a mathematical analysis calculating the likelihood of occurrence of terrorist incidents in three common real-life scenarios arising in peace-keeping operations.",
author = "Verma, {Dinesh C.} and Archit Verma and Diane Felmlee and Gavin Pearson and Roger Whitaker",
note = "Funding Information: This research was sponsored by the U.S. Army Research Laboratory and the U.K. Ministry of Defence under Agreement Number W911NF-16-3-0001. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Army Research Laboratory, the U.S. Government, the U.K. Ministry of Defence or the U.K. Government. The U.S. and U.K. Governments are authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon. Content includes material subject to {\textcopyright} Crown copyright (2017), Dstl. This material is licensed under the terms of the Open Government Licence except where otherwise stated. To view this licence, visit http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3 or write to the Information Policy Team, The National Archives, Kew, London TW9 4DU, or email: psi@nationalarchives.gsi.gov.uk{"}. Dstl/CP101011. Publisher Copyright: {\textcopyright} COPYRIGHT SPIE.; 8th Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR ; Conference date: 10-04-2017 Through 13-04-2017",
year = "2017",
doi = "10.1117/12.2264909",
language = "English (US)",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Tien Pham and Kolodny, {Michael A.}",
booktitle = "Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VIII",
address = "United States",
}