A Survey on the Application of Machine Learning in Predicting the Accuracy of Terrorist Attacks

Swathi R, Karthikeyan T

Abstract: Terrorist attacks pose a significant threat to global security, making accurate prediction and prevention crucial. Machine learning techniques have emerged as powerful tools for analyzing and predicting terrorist activities. In this survey paper, we explore the use of machine learning algorithms for predicting terrorist attacks' accuracy. We review various approaches, datasets, and evaluation metrics employed in this domain. Additionally, we discuss challenges and future directions for improving the accuracy of terrorist attack prediction using machine learning.

Keywords: Terrorist attacks, machine learning, prediction, accuracy, classification algorithms, feature selection, evaluation metrics, datasets