AI-Driven Counter-Terrorism: Enhancing Global Security Through Advanced Predictive Analytics-Reference-Cited by-同舟云学术

AI-Driven Counter-Terrorism: Enhancing Global Security Through Advanced Predictive Analytics

Published:2023 Issue: Volume:11 Page:135864-135879
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Khan Fahad Ali¹,Li Gang¹^ORCID,Khan Anam Nawaz²^ORCID,Khan Qazi Waqas²^ORCID,Hadjouni Myriam³^ORCID,Elmannai Hela⁴^ORCID

Affiliation:

1. College of Urban and Environmental Sciences, Northwest University, Xi'an, People's Republic of China (PRC)

2. Department of Computer Engineering, Big-Data Research Center, Jeju National University, P.O. Box 84428, Jeju, Republic of Korea

3. Department of Computer Sciences, College of Computer and Information Science, Princess Nourah bint Abdulrahman Universit, P.O. Box 84428, Riyadh, Saudi Arabia

4. Department of Information Technology, College of Computer and Information Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, Saudi Arabia

Funder

Princess Nourah bint Abdulrahman University Researchers

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10328769.pdf?arnumber=10328769

Reference33 articles.

1. Economics of Terrorism and Counter-Terrorism Measures

2. Terrorism and environmental sustainability: Empirical evidence from the MENA region

3. Extremism immunity through artificial intelligence networks: Extremism awareness and social intelligence

4. Prediction of terrorist activities in Nigeria using machine learning models;Odeniyi;Innovations,2022

5. Open source intelligence extraction for terrorism‐related information: A review

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