Combating Terrorism in India through Prediction of Risk Associated With an Attack Using Investigative Data Mining Techniques

Enhancing Counter-terrorism through Investigative Data Mining and Machine Learning Techniques

Abstract

After “911” terrorist attacks, more advanced information technologies have been developed to counter-terrorism domain to enhance the performance of early warning system. Machine learning-based data mining is applied to predict terrorist activities hidden in terrorist incidents. Data mining classification techniques are mostly used to handle the problem of terrorism in India. An Ensemble Model building approach to classify worldwide terrorist attacks for the prediction of the fatality-risk associated with the terrorist attacks by utilizing different classifiers such as Decision Tree, Naïve Bayes, Lazy classifier IBK (k-NN) and Decision Table is used in the study. These algorithms are implemented in this study using WEKA a data mining tool and have attained fair accuracies in the perspective of classifiers’ performance.