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Paper details
Number 3 - September 2022
Volume 32 - 2022
ATiPreTA: An analytical model for time-dependent prediction of terrorist attacks
Oussama Kebir, Issam Nouaouri, Lilia Rejeb, Lamjed Ben Said
Abstract
In counter-terrorism actions, commanders are confronted with difficult and important challenges. Their decision-making
processes follow military instructions and must consider the humanitarian aspect of the mission. In this paper, we aim to
respond to the question: What would the casualties be if governmental forces reacted in a given way with given resources? Within a similar context, decision-support systems are required due to the variety and complexity of modern attacks as well as the enormous quantity of information that must be treated in real time. The majority of mathematical models are not suitable for real-time events. Therefore, we propose an analytical model for a time-dependent prediction of terrorist attacks (ATiPreTA). The output of our model is consistent with casualty data from two important terrorist events known in Tunisia: Bardo and Sousse attacks. The sensitivity and experimental analyses show that the results are significant. Some operational insights are also discussed.
Keywords
terrorist attacks, attack classification, mathematical modeling, dynamic behavior simulation, damage prediction