[Objective] This study modifies Naive Bayes Classifier according to the features of
counterterrorism intelligence, aiming to provide a simple and practical way to categorize …

This paper establishes a relatively complete theoretical framework, with multi-disciplinary
perspective. Intelligence-led counterterrorism framework based on data mining can be …

Terrorism has virtually invaded our day to day lives. We can't imagine of passing a day
without a terrorist attack in any part of the country that has brought in irreparable loss to …

Terrorist attacks are the biggest challenging problem for the mankind across the world,
which need the wholly attention of the researchers, practitioners to cope up deliberately. To …

Terrorism has become one of the most tedious problems to deal with and a prominent threat
to mankind. To enhance counter-terrorism, several research works are developing efficient …

Terrorism has become one of the most tedious problems to deal with and a prominent threat
to mankind. To enhance counter-terrorism, several research works are developing efficient …

Terrorist attacks pose a great threat to global security, and their analysis and prediction are
imperative. Considering the high frequency of terrorist attacks and the inherent difficulty in …

Terrorist attacks can be analysed and predicted with detailed historical data for better
prevention and early warning. In this paper, we use the Global Terrorism Database (GTD) to …

One of the biggest dangers to society today is terrorism, where attacks have become one of
the most significant risks to international peace and national security. Big data, information …

The objective on this paper is to propose a conceptual classi cation for terrorist attacks that
presents a preprocessing for Arti cial Intelligence classi cation model based on two layers …