Machine Learning Techniques to Predict Terrorist Attacks : Exemplified by Jama'at Nasr al-Islam wal Muslimin
Language: English
Published by Springer, 2025
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 56.45
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Add to basketItem description from seller
Druck auf Anfrage Neuware - Printed after ordering - One of the most influential actors in spreading Islamist violence across the Sahel is Jama at Nasr Al Islam Wal Muslimin (JNIM).This book provides the first systematic quantitative analysis of JNIM s behavior by analyzing a 12-year database of JNIM s attacks and the environment surrounding JNIM. This book leverages AI/ML predictive models to accurately predict almost 40 types of attacks using over 80 independent variables.This book describes a set of temporal probabilistic rules that state that when the environment in which the group operates satisfies some conditions, then an attack of a certain type will likely occur in the next N months. This provides a deep, easy to comprehend understanding of the conditions under which JNIM carries various kinds of attacks up to 6 months into the future. This book will serve as an invaluable guide to scholars (computer scientists, political scientists, policy makers). Military officers, intelligence personnel, and government employees, who seek to understand, predict, and eventually mitigate attacks by JNIM and bring peace to the nations of Mali, Burkina Faso, and Niger will want to purchase this book as well. …
Seller Inventory # 9783031931734
- Title
- Machine Learning Techniques to Predict Terrorist Attacks : Exemplified by Jama'at Nasr al-Islam wal Muslimin
- Author
- Chiara Pulice
- Publisher
- Springer
- Publication year
- 2025
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 3031931734
- ISBN 13
- 9783031931734
- Item weight
- 393 grams
- Dimensions
- 241x160x14 mm
One of the most influential actors in spreading Islamist violence across the Sahel is Jama’at Nasr Al Islam Wal Muslimin (JNIM).This book provides the first systematic quantitative analysis of JNIM’s behavior by analyzing a 12-year database of JNIM’s attacks and the environment surrounding JNIM. This book leverages AI/ML predictive models to accurately predict almost 40 types of attacks using over 80 independent variables.
This book describes a set of temporal probabilistic rules that state that when the environment in which the group operates satisfies some conditions, then an attack of a certain type will likely occur in the next N months. This provides a deep, easy to comprehend understanding of the conditions under which JNIM carries various kinds of attacks up to 6 months into the future.
This book will serve as an invaluable guide to scholars (computer scientists, political scientists, policy makers). Military officers, intelligence personnel, and government employees, who seek to understand, predict, and eventually mitigate attacks by JNIM and bring peace to the nations of Mali, Burkina Faso, and Niger will want to purchase this book as well.
"Synopsis" may belong to another edition of this title.
About the Author
Laura Mostert is an officer in the Royal Netherlands Air Force with a background in war studies and cyber security governance.
Roy Lindelauf is the Chair Data Science in Military Operations at Faculty of Military Sciences at Netherlands Defence Academy and an Endowed Chair Data Science for Safety, Security at the Department of Cognitive Science & Artificial Intelligence at Tilburg School of Humanities and Digital Sciences. He is also Head of Data Science Center of Excellence at Netherlands Ministry of Defence.
Chiara Pulice is a Senior Research Associate in computer science with Northwestern University, Evanston, IL, USA. Her research interests include counter-terrorism and machine learning. She received the Ph.D. degree in computer and systems engineering from the University of Calabria, Cosenza, Italy, in 2015.
Marnix Provoost is an active duty officer in the Royal Netherlands Army. He holds a Master’s degree in Military Strategic Studies and is currently positioned at the Netherlands Defence Academy as a fulltime PhD student. His research is focused on insurgencies and their analogies with state formation.
Priyanka Amin has recently finished her undergraduate degree in computer science and global history at Northwestern University.
V.S. Subrahmanian is the Walter P. Murphy Professor of Computer Science and Buffett Faculty Fellow in the Buffett Institute for Global Affairs at Northwestern University where he also heads the Northwestern Security & AI Lab. He is one of the world’s foremost experts at the intersection of AI and Security matters ranging from counterterrorism to cybersecurity to border issues and warfare. An elected Fellow of AAAI and AAAS, he has previously served as Director of the Institute for Security, Technology, and Society at Dartmouth College and as Director of the University of Maryland Institute for Advanced Computer Studies.
"About the title" may belong to another edition of this title.
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