AI-driven Cyber Risk Management
Description
This book provides a comprehensive exploration of how artificial intelligence (AI) is revolutionizing cyber risk management, offering advanced methodologies to identify, assess, quantify, and mitigate threats effectively. Through the integration of AI, big data analytics, and emerging technologies, this book presents cutting-edge approaches to addressing cyber risks. Readers will gain insights into how AI enhances threat detection, fraud prevention, risk quantification, and incident response, equipping businesses to anticipate, measure, and mitigate cyber disruptions with greater precision.
In today's digital landscape, businesses increasingly depend on complex cyber systems including cloud computing and data infrastructure, enterprise systems, financial and payment, and other operational systems, which make them susceptible to a wide range of risks beyond conventional security threats. Downtimes, system failures, data breaches, and cyber infrastructure outages can cause significant operational, reputational, and financial disruptions. To navigate these challenges, organizations must move beyond traditional risk management approaches and adopt AI-driven solutions for more proactive and intelligent cyber risk management.
Structured around key aspects of AI-driven cyber risk management, the book begins with foundational principles before delving into the rise of AI in cyber risk management, the role of big data in risk analysis, and the application of AI in threat intelligence and fraud detection. Readers will explore AI-powered risk quantification models, automated mitigation strategies, and the integration of AI into cybersecurity infrastructure, business continuity planning, and disaster recovery. Industry-specific case studies offer real-world insights into AI's impact across different sectors, while discussions on emerging technologies, such as IoT, blockchain, large language models, advanced machine learning, and explainable AI, highlight the future trajectory of AI in cyber risk management.
Aimed at professionals, researchers, and students, this book balances technical depth with practical clarity, making it an essential guide for those seeking to bridge the gap between AI innovation and real-world cyber risk applications. By addressing both the potential and challenges of AI-driven solutions, it presents a forward-thinking strategy for building resilient, AI-powered cyber risk management frameworks.
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Persons
Dr. Hooman Razavi is currently an associate research assistant in the Department of Engineering Science at Tecnológico de Monterrey, Mexico, and the University of Ottawa. He holds a B.Sc. in computer engineering, an M.Sc. in artificial intelligence, and a Ph.D. in engineering science. Dr. Razavi has served as a sessional lecturer at University Canada West. He has published widely in conferences, book chapters, and journal papers in the fields of applied AI and cyber risk management. His professional experience also includes roles as a senior data scientist and consultant in several fintech firms. He currently serves on the editorial board of the International Journal of Cybersecurity and Risk Assessment and is associate editor of Transactions on Swarm and Evolutionary Learning. Dr. Razavi has the role of reviewer for numerous journals, including IEEE Transactions on Artificial Intelligence, IEEE Communications Magazine, Information Systems Journal, Expert Systems with Applications, Engineering Applications of Artificial Intelligence, Applied Soft Computing, Cyber security and Applications, and Digital Business. Additionally, he has served on technical program committees for leading conferences, such as ICLR, NeurIPS, AISTATS, IEEE WINCOM, IEEE CSR, IEEE GCAIoT, IEEE CSNet, and ICMI. Dr. Razavi has also been a keynote speaker at numerous international conferences and has conducted multiple webinars. Dr. Muriel Figueredo Franco has experience as a researcher and consultant in cybersecurity planning and risk quantification. In his research career, he has participated in different multidisciplinary projects with teams of experts in cybersecurity, computer networks, project management, and economics, with more than 70 published articles and two co-authored patents. His work supports the discussion of cybersecurity's economic aspects, thus aiding better planning and investment in cybersecurity. Also, he worked as a cybersecurity consultant to build risk quantification approaches as a product for international companies. Muriel holds a Ph.D. (Summa cum laude) in Computer Science from the University of Zurich (UZH), Switzerland, an MBA in Project Management from the University of São Paulo (USP), Brazil, a Master's degree in computer science from the Federal University of Rio Grande do Sul (UFRGS), Brazil, and a Bachelor's degree in computer science from the Federal University of Pelotas (UFPEL), Brazil, in 2014. He was also a Postdoctoral researcher at UFRGS from 2023 to 2025. Furthermore, he served as a member of the Technical Program Committee (TPC) for many cybersecurity and network management events, such as IEEE GLOBECOM, IEEE/IFIP NOMS, and the Brazilian Symposium of Cybersecurity (SBSeg). Additionally, Muriel served as a reviewer for top journals, including IEEE Communications Magazine (COMMAG), Computers & Security (COSE), and IEEE Transactions on Network and Service Management (TNSM). Dr. Mariya Ouaissa is currently a Professor in Cybersecurity and Networks at Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakech, Morocco. She has a Ph.D., graduating in 2019 in computer science and networks from ENSAM-Moulay Ismail University, Meknes, Morocco. She is a Networks and Telecoms Engineer, graduating in 2013 from National School of Applied Sciences Khouribga, Morocco. She is a Co-Founder and IT Consultant at the IT Support and Consulting Center. She worked for School of Technology of Meknes Morocco as a Visiting Professor from 2013 to 2021. She is a member of the International Association of Engineers and International Association of Online Engineering, and since 2021 she has been an "ACM Professional Member". She is an expert reviewer with Academic Exchange Information Centre (AEIC) and Brand Ambassador with Bentham Science. She has served and continues to serve on technical program and organizer committees of several conferences and events and has organized many symposiums/workshops/conferences as a general chair; she is also a reviewer for numerous international journals. Dr. Ouaissa has made contributions in the fields of information security and privacy, Internet of Things security, and wireless and constrained networks security. Her main research topics are IoT, M2M, D2D, WSN, cellular networks, and vehicular networks. She has published over 90 papers (book chapters, international journals, and conferences/workshops), 35 edited books, and 10 special issues as guest editor. Dr. Mariyam Ouaissa is currently an Assistant Professor in Networks and Systems at ENSA, Chouaib Doukkali University, El Jadida, Morocco. She received her Ph.D. degree in 2019 from National Graduate School of Arts and Crafts, Meknes, Morocco and her Engineering Degree in 2013 from the National School of Applied Sciences, Khouribga, Morocco. She is a communication and networking researcher and practitioner with industry and academic experience. Dr Ouaissa's research is multidisciplinary and focuses on Internet of Things, M2M, WSN, vehicular communications and cellular networks, security networks, congestion overload problems and resource allocation management and access control. She serves as a reviewer for international journals and conferences including as IEEE Access, Wireless Communications and Mobile Computing. Since 2020, she has been a member of "International Association of Engineers IAENG" and "International Association of Online Engineering", and since 2021, she has been an "ACM Professional Member". She has published more than 70 research papers (this includes book chapters, peer-reviewed journal articles, and peer-reviewed conference manuscripts), 20 edited books, and 6 special issues as guest editor. She has served on Program Committees and Organizing Committees of several conferences and events and has organized many symposiums/workshops/conferences. Dr. Gautam Srivastava (Senior Member, IEEE) received his B.Sc. degree from Briar Cliff University, USA, in 2004, and his M.Sc. and Ph.D. degrees from the University of Victoria, Victoria, BC, Canada, in 2006 and 2012, respectively. Then, he taught for three years with the Department of Computer Science, University of Victoria, where he was regarded as one of the top undergraduate professors in computer science course instruction. From there, in 2014, he joined a tenure-track position at Brandon University, Brandon, MB, Canada, where he is currently active in various professional and scholarly activities. He was promoted to the rank of Professor in 2023. He is active in research in the field of computer security and privacy with a specialization in cybersecurity. In his ten-year academic career, he has published a total of 450 papers in high-impact conferences in many countries and high-status journals (SCI and SCIE). He has delivered invited guest lectures and keynotes on cybersecurity, cloud computing, the Internet of Things, and cryptography at many international conferences and universities. He is an editor of several international scientific research journals. He currently has active research projects with other academics internationally.
Content
1. Foundations of Cyber Risk Management 2. The Rise of AI and Risk Management 3. The Future of Cyber Risk Management in an AI-driven World 4. Artificial Intelligence in Cyber Risk Management: Revolutionizing Threat Detection and Resilience 5. AI for Threat Detection and Intelligence
6. Empowering Cybersecurity with AI: Advanced Threat Detection, Predictive Intelligence, and Real-time Defense 7. AI-powered Risk Mitigation and Intelligent Incident Response in Cybersecurity 8. Challenges in Cyber Risk Analysis Using Big Data and AI Models 9. Rising Impact of AI in Cyber Risk Management in the Context of Small- and Medium-sized Enterprises 10. Toward Resilient Cyber Defense: Integrating AI and Blockchain for Smart Risk Management 11. Advanced Approaches to Fraud Detection and Financial Risk Mitigation Using Intelligent Analytics 12. XAI-driven Approaches to Detect Financial Frauds and Mitigate Risk 13. MIND-SHIELD: A Multi-Intelligence Deep Learning Framework for Hierarchical Threat Detection and Zero-shot Situational Intelligence Process 14. Integrating AI into Cybersecurity Infrastructure: A Case Study on Dynamic C&C Server Architecture (PhantomNet) 15. Automating Cybersecurity Risk Assessments with a Modern Penetration Testing Approach (PenTest Pro)
