Data Analysis and Risk Modelling for Terrorism Prevention:

In the field of terrorism prevention, data analysis plays a critical role in developing predictive models to address the growing complexity of modern terrorist tactics. This book examines the challenges, methods, and ethical implications of utilizing data science and artificial intelligence (AI) in counter-terrorism efforts. By exploring advanced analytical models, the work provides insights into identifying patterns in terrorist activities and predicting potential threats. Focused on the integration of big data, machine learning, and real-time analysis, the book outlines how these technologies can assist in proactive terrorism prevention. It also delves into the ethical considerations that arise from collecting and analyzing sensitive data in such high-stakes situations.

Inhalt
1 Introduction 1.1 Problem definition and research question 1.2 Objectives and approach 2 Literature research - data analysis in the context of terrorism prevention 2.1 Data science and artificial intelligence 2.2 Data analysis models 2.3 Modern terrorism 2.4 Factors in the prevention of terrorism 2.5 Challenges in data analysis 2.6 Hypotheses and concept of the work 3 Methodology and data basis 3.1 Data records 3.2 Methodological approach 3.3 Research ethics 4 Analysis model and interpretation 4.1 Data processing and preparation 4.2 Cluster and classification analysis 4.3 Deep learning 4.4 Visualisation of the results 5 Discussion 5.1 Feasibility and technical realisation 5.2 Interpretation of the results and recommendations for action 6 Conclusion IV Bibliography