A framework for agro-terrorism intentions detection using overt data sources

Eli Rohn; Gil Erez

doi:10.1016/j.techfore.2013.06.008

A framework for agro-terrorism intentions detection using overt data sources

Eli Rohn, Gil Erez

Department of Software and Information Systems Engineering

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

Agro-terrorism is a hostile attack, towards an agricultural environment, including infrastructures and processes, in order to significantly damage national and international political interests. This article provides a framework for reducing agro-terrorism-related risks by either means of foresight (prevention) or early detection of exotic/foreign pathogenic agents and their dispersion patterns. It focuses on intention detection using overt data sources on the World Wide Web as they relate to agro-terrorism threats. The paper defines agro-terrorism, examines data characteristics, identifies weaknesses among the intelligence community that must be addressed, then integrates the classical intelligence cycle for early detection that may lead to prevention of such acts.

Original language	English
Pages (from-to)	1877-1884
Number of pages	8
Journal	Technological Forecasting and Social Change
Volume	80
Issue number	9
DOIs	https://doi.org/10.1016/j.techfore.2013.06.008
State	Published - 1 Nov 2013

Keywords

Agroterrorism
Authorship attribution
Cyber-terrorism
Digital shadow
Intelligence
Text mining

ASJC Scopus subject areas

Business and International Management
Applied Psychology
Management of Technology and Innovation

UN SDGs

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

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10.1016/j.techfore.2013.06.008

Cite this

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abstract = "Agro-terrorism is a hostile attack, towards an agricultural environment, including infrastructures and processes, in order to significantly damage national and international political interests. This article provides a framework for reducing agro-terrorism-related risks by either means of foresight (prevention) or early detection of exotic/foreign pathogenic agents and their dispersion patterns. It focuses on intention detection using overt data sources on the World Wide Web as they relate to agro-terrorism threats. The paper defines agro-terrorism, examines data characteristics, identifies weaknesses among the intelligence community that must be addressed, then integrates the classical intelligence cycle for early detection that may lead to prevention of such acts.",

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AB - Agro-terrorism is a hostile attack, towards an agricultural environment, including infrastructures and processes, in order to significantly damage national and international political interests. This article provides a framework for reducing agro-terrorism-related risks by either means of foresight (prevention) or early detection of exotic/foreign pathogenic agents and their dispersion patterns. It focuses on intention detection using overt data sources on the World Wide Web as they relate to agro-terrorism threats. The paper defines agro-terrorism, examines data characteristics, identifies weaknesses among the intelligence community that must be addressed, then integrates the classical intelligence cycle for early detection that may lead to prevention of such acts.

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KW - Authorship attribution

KW - Cyber-terrorism

KW - Digital shadow

KW - Intelligence

KW - Text mining

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JF - Technological Forecasting and Social Change

IS - 9

ER -

A framework for agro-terrorism intentions detection using overt data sources

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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