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E-TGPS: Enhanced Terrorist Group Prediction System for Counter Terrorism

by Abhishek Sachan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 117 - Number 24
Year of Publication: 2015
Authors: Abhishek Sachan
10.5120/20704-3633

Abhishek Sachan . E-TGPS: Enhanced Terrorist Group Prediction System for Counter Terrorism. International Journal of Computer Applications. 117, 24 ( May 2015), 24-28. DOI=10.5120/20704-3633

@article{ 10.5120/20704-3633,
author = { Abhishek Sachan },
title = { E-TGPS: Enhanced Terrorist Group Prediction System for Counter Terrorism },
journal = { International Journal of Computer Applications },
issue_date = { May 2015 },
volume = { 117 },
number = { 24 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = { 24-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume117/number24/20704-3633/ },
doi = { 10.5120/20704-3633 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:00:18.525077+05:30
%A Abhishek Sachan
%T E-TGPS: Enhanced Terrorist Group Prediction System for Counter Terrorism
%J International Journal of Computer Applications
%@ 0975-8887
%V 117
%N 24
%P 24-28
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Terrorist group prediction using historical data of terrorist incidents has been less explored due to the lack of meticulous terrorist data which contains terrorist group's attacks and activities information. There are many reasons for less exploration like its confidentiality & sensitivity. This paper presents an enhanced system that helps to predict the terrorist groups involved in the attack under investigation named E-TGPS. This system initially learns similarities of terrorist activities from various past terrorist incidents to predict the responsible group. This system can be considered as a vital tool for security agencies and intelligence analysts, by providing more reliable and predictive solutions to take effective counter-terrorism measures. The system has been validated by experimental results. The overall performance of the system displays a fair degree of accuracy. This paper also lays emphases on the meticulous analysis of optimal parameters weight estimation, to improve the predictive accuracy of the system.

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Index Terms

Computer Science
Information Sciences

Keywords

Terrorist groups pattern matching prediction terrorism counter-terrorism group detection privacy security.

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