Security Intelligence and SDG16: Applying Machine Learning for Peaceful and Inclusive Societies
In today’s rapidly evolving digital landscape, traditional security frameworks struggle to keep pace with increasingly sophisticated cyber threats. As cybercrime and espionage surge, the need for innovative, predictive solutions has never been more urgent. Machine learning offers a proactive approach to threat detection, responsive security measures, and access management, supporting global peace and justice in alignment with the United Nations’ Sustainable Development Goal 16 (SDG 16).

Security Intelligence and SDG16: Applying Machine Learning for Peaceful and Inclusive Societies presents a timely exploration of how machine learning can enhance security intelligence practices. This edited collection brings together insights from experts worldwide, covering core topics such as advanced threat detection algorithms, predictive risk analytics, and automated access control. Beyond technical applications, the volume delves into the ethical, legal, and social dimensions of AI-driven security, providing a comprehensive framework that aligns security intelligence advancements with the SDG 16 objectives of fostering peaceful, inclusive societies. Addressing the needs of policymakers, cybersecurity professionals, and academic researchers, this collection provides the theoretical knowledge and practical insights essential for building ethical and effective security systems.

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Security Intelligence and SDG16: Applying Machine Learning for Peaceful and Inclusive Societies
In today’s rapidly evolving digital landscape, traditional security frameworks struggle to keep pace with increasingly sophisticated cyber threats. As cybercrime and espionage surge, the need for innovative, predictive solutions has never been more urgent. Machine learning offers a proactive approach to threat detection, responsive security measures, and access management, supporting global peace and justice in alignment with the United Nations’ Sustainable Development Goal 16 (SDG 16).

Security Intelligence and SDG16: Applying Machine Learning for Peaceful and Inclusive Societies presents a timely exploration of how machine learning can enhance security intelligence practices. This edited collection brings together insights from experts worldwide, covering core topics such as advanced threat detection algorithms, predictive risk analytics, and automated access control. Beyond technical applications, the volume delves into the ethical, legal, and social dimensions of AI-driven security, providing a comprehensive framework that aligns security intelligence advancements with the SDG 16 objectives of fostering peaceful, inclusive societies. Addressing the needs of policymakers, cybersecurity professionals, and academic researchers, this collection provides the theoretical knowledge and practical insights essential for building ethical and effective security systems.

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Security Intelligence and SDG16: Applying Machine Learning for Peaceful and Inclusive Societies

Security Intelligence and SDG16: Applying Machine Learning for Peaceful and Inclusive Societies

Security Intelligence and SDG16: Applying Machine Learning for Peaceful and Inclusive Societies

Security Intelligence and SDG16: Applying Machine Learning for Peaceful and Inclusive Societies

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Overview

In today’s rapidly evolving digital landscape, traditional security frameworks struggle to keep pace with increasingly sophisticated cyber threats. As cybercrime and espionage surge, the need for innovative, predictive solutions has never been more urgent. Machine learning offers a proactive approach to threat detection, responsive security measures, and access management, supporting global peace and justice in alignment with the United Nations’ Sustainable Development Goal 16 (SDG 16).

Security Intelligence and SDG16: Applying Machine Learning for Peaceful and Inclusive Societies presents a timely exploration of how machine learning can enhance security intelligence practices. This edited collection brings together insights from experts worldwide, covering core topics such as advanced threat detection algorithms, predictive risk analytics, and automated access control. Beyond technical applications, the volume delves into the ethical, legal, and social dimensions of AI-driven security, providing a comprehensive framework that aligns security intelligence advancements with the SDG 16 objectives of fostering peaceful, inclusive societies. Addressing the needs of policymakers, cybersecurity professionals, and academic researchers, this collection provides the theoretical knowledge and practical insights essential for building ethical and effective security systems.


Product Details

ISBN-13: 9781837082834
Publisher: Emerald Publishing Limited
Publication date: 02/16/2026
Pages: 320
Product dimensions: 5.98(w) x 9.02(h) x (d)

About the Author

Christian Kaunert is Professor of International Security at Dublin City University, Ireland. He is also Professor of Policing and Security, as well as Director of the International Centre for Policing and Security at the University of South Wales. He is Jean Monnet Chair, Director of the Jean Monnet Centre of Excellence and Director of the Jean Monnet Network on EU Counter-Terrorism (www.eucter.net).

Anjali Raghav is a legal professional and accomplished academic, currently a Research Scholar at the Sharda School of Law, Sharda University, Greater Noida, India.

Dr. Bhupinder Singh working as Professor in Sharda School of Law, Sharda UniversityGreater Noida, India. Also, Honorary Professor in University of South Wales UK, Santo Tomas UniversityTunja, Colombia and North Bangkok University, Thailand.

Table of Contents

Chapter 1. AI-Driven Cybersecurity Strengthening Digital Frontiers: Opportunities and Challenges; Hamed Taherdoost, Anjali Raghav, and Richa Raghav
Chapter 2. Artificial Intelligence (AI) in Law Enforcement and Criminal Activities: A Dual-Use Dilemma; Kamalesh Ravesangar and Shayut Pavapanunkul
Chapter 3. Conceptualizing AI for Tribal Development- Roadmap for Inclusive Future of Indigenous Groups; Sowmya G., Aruna Polisetty, Lalitha Nammi, and Isabel B. Franco
Chapter 4. Ethical AI in Security Intelligence: Balancing Innovation, Privacy and Security; Dorottya Edina Kozma and Saurabh Chandra
Chapter 5. Fraud Detection and AI to Safeguarding Financial System; Bhupinder Singh, Rahul J. Nikam, Soufiane Ouariach, and Ashima Jain
Chapter 6. Governance, Moral Imperatives and Threat Detection: Ethical AI in Security Intelligence; Pranjal Chaturvedi, Suhasini, and Bhupinder Singh
Chapter 7. Harnessing Al and Cybersecurity in Strengthening Digital Governance for Peace and Security; Christian Kaunert, Bhupinder Singh, and Fatima Zahra Ouariach
Chapter 8. Justice and Human Rights with AI, Predictive Policing and Security Intelligence in Criminal Justice; Kittisak Wongmahesak and Lipsy
Chapter 9. Policy Framework for AI-Driven Security Intelligence: Challenges and Ethical Considerations; Laeeq R. Janjua, Sahil Lal, Manmeet Kaur Arora, Ashima Jain, Anjali Raghav, and Saquib Ahmed
Chapter 10. Regulatory Foundation of AI-driven Security in Education, Healthcare and National Security; Saurabh Chandra and Ismail Suardi Wekke
Chapter 11. Securing the Future: The Intersection of Artificial Intelligence and Cyber Security; Abhay Raj Singh and Urmila Yadav
Chapter 12. Upholding Accountability and Ethics in AI-Driven Predictive Policy; Hammouch Hind
Chapter 13. Artificial Intelligence for Cybersecurity: A New Era of Protection; Toshi Rattan, Nituja Singh, and Olawunmi Opeyemi Obisesan
Chapter 14. Unleashing Identity Security with AI and Access Policy Management; Bhupinder Singh and Uday Kumar Ghosh

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