AI-Driven Cybersecurity Finance

Abstract and Manuscript submision: https://easychair.org/conferences?conf=aidrivencybersecurit0  

This book aims to equip financial professionals and banking experts with the knowledge to develop and implement robust security systems. It explores current trends, tools, and advanced technologies, and how they can foster the growth of a sustainable finance ecosystem. It is also designed for a broad audience of specialists, analysts, engineers, scholars, researchers, academics, professionals, and students, providing a platform to share and develop new ideas, methodologies, technologies, approaches, models, frameworks, theories, and practices. The goal is to address the complex challenges of integrating AI, blockchain, big data, cloud computing, and cybersecurity within the digital financial ecosystem.

You are invited to contribute chapters and papers and the scope of the book includes but is not limited to the following topics:

Submission Guidelines

All chapters or papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:

• Abstract registration deadline: Oct 30, 2025
• Acceptance notification: Oct 30, 2025
• Manuscript submission deadline: Nov 15, 2025
• Springer Nature AG agreement: Nov 30, 2025

List of Topics

• The Role of Artificial Intelligence in the Digital Financial Age: This chapter sets the stage by exploring the fundamental ways artificial intelligence is transforming the financial industry, from enhancing customer experience to streamlining operations, and introduces the inherent cybersecurity implications of this digital evolution.

• Challenges and Opportunities in the Financial Internet of Things (FIoT): This chapter delves into the expanding world of connected devices within finance, examining the unique security vulnerabilities introduced by the FIoT and the potential for AI to both exacerbate and mitigate these risks.

• A Strategic Approach to Adopting and Integrating AI Cybersecurity Solutions: This chapter provides a practical framework for financial institutions to strategically plan, implement, and integrate AI-powered cybersecurity tools and processes into their existing security infrastructure.

• Preparing for the Future of AI-Enabled Financial Crime: This chapter looks ahead, analyzing how cybercriminals are likely to leverage AI in their attacks and outlining proactive strategies that financial institutions can adopt to anticipate and defend against these emerging threats.

• Advancements and Challenges of AI in Cybersecurity in Finance Sector: This chapter offers a balanced perspective on the current state of AI in financial cybersecurity, highlighting the significant advancements made while also addressing the key limitations and challenges that need to be overcome.

• AI-Driven Cybersecurity in Banking and Finance Sectors: This chapter focuses specifically on the application of AI to enhance cybersecurity within the banking and broader finance sectors, exploring real-world use cases and the tangible benefits achieved.

• Beyond Detection: AI for Proactive and Resilient Cybersecurity: This chapter moves beyond traditional reactive security measures, exploring how AI can enable proactive threat hunting, predictive analysis, and the development of more resilient financial systems capable of withstanding attacks.

• The Role of Human Expertise in an Era of Intelligent Financial Security: This chapter emphasizes the crucial and evolving role of human cybersecurity professionals in a landscape increasingly dominated by AI, highlighting the synergy between human intelligence and artificial intelligence.

• The Transformation of Financial Security Operations with Artificial Intelligence: This chapter examines how AI is revolutionizing Security Operations Centers (SOCs) within financial institutions, leading to greater automation, efficiency, and improved incident response capabilities.

• Biologically Inspired AI for Robust Cyber Defense in Finance Sector: This chapter explores the cutting-edge field of biologically inspired AI algorithms and their potential to create more adaptive, resilient, and robust cyber defense mechanisms specifically tailored for the financial industry.

• Building Resilient Systems Against AI-Driven Threats in Finance Sector: This chapter focuses on architectural and systemic approaches to building financial systems that are inherently more resistant to sophisticated, AI-powered cyberattacks.

• Combating Ransomware and Extortion Attacks on Financial Institutions: This chapter specifically addresses the growing threat of ransomware and extortion in the financial sector, detailing how AI can be used to both prevent and respond to these attacks effectively.

• Countering Adversarial Attacks on AI-Powered Security Systems: This chapter delves into the critical area of adversarial AI, exploring how malicious actors can target and manipulate AI security systems and outlining strategies to defend against such attacks.

• Detecting and Mitigating Insider Threats with Artificial Intelligence: This chapter examines the unique challenge of insider threats within financial institutions and how AI-powered behavioral analytics and anomaly detection can be used to identify and mitigate these risks.

• Enhancing Anti-Money Laundering (AML) and Know Your Customer (KYC) Processes with AI: This chapter explores the significant potential of AI to improve the efficiency, accuracy, and effectiveness of AML and KYC processes within the financial sector, bolstering regulatory compliance and fraud prevention.

• Explainable AI (XAI) for Transparent and Trustworthy Security Decisions: This chapter highlights the importance of transparency in AI-driven security decisions, particularly in the highly regulated financial industry, and explores the role of Explainable AI (XAI) in building trust and accountability.

• Federated Learning for Collaborative Cybersecurity in Distributed Systems: This chapter introduces the concept of federated learning and its potential to enable collaborative cybersecurity efforts among financial institutions while preserving data privacy and security.

• From Reactive to Predictive: Leveraging AI for Advanced Cyber Defense: This chapter further elaborates on the shift towards predictive cybersecurity in finance, showcasing how AI can analyze historical data and identify patterns to anticipate and prevent future attacks.

• Generative AI for Cyber Deception and Defense in Finance System: This chapter explores the emerging applications of generative AI in cybersecurity for the financial system, including its use in creating realistic decoys and enhancing defensive strategies.

• Harnessing Federated Learning for Collaborative Security: This chapter provides a deeper dive into the practical applications and challenges of implementing federated learning frameworks for enhanced cybersecurity collaboration within the financial sector.

• Leveraging AI for Enhanced Risk Assessment and Management: This chapter focuses on how AI can revolutionize risk assessment and management within financial institutions, providing more accurate, dynamic, and comprehensive insights into potential vulnerabilities.

• Protecting Data and Ensuring Privacy in the Age of Intelligent Analytics: This chapter addresses the critical concerns of data protection and privacy in the context of AI-driven analytics within the financial industry, exploring techniques and best practices for secure data handling.

• Securing the Digital Frontier: AI for Endpoint Protection and Response: This chapter examines the crucial role of AI in enhancing endpoint security within financial institutions, improving detection, prevention, and response to threats targeting individual devices.

• The Evolving Landscape of AI in Cybersecurity: Threats and Opportunities: This chapter provides a concluding overview of the dynamic interplay between AI and cybersecurity in the financial sector, summarizing key trends, emerging threats, and future opportunities.

• Towards Autonomous and Intelligent Financial Security Infrastructure: This chapter envisions the future of financial cybersecurity, exploring the potential for developing more autonomous and self-learning security systems powered by advanced artificial intelligence.

Publication

AI-Driven-Cybersecurity-Finance-2025 proceedings will be published in 2025 by Springer Nature

Contact

All questions about submissions should be emailed to

Prof. Dr. Alex Khang

• Professor of IT, D.Sc., D.Litt., M.B.A, AI and Data Scientist, Global Research Institute of Technology and Engineering, North Carolina, United States
• Email: alex.khang@outlook.com
• ORCID: 0000-0001-8379-4659

Publication Charge

No Publication Charge

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Benefits for Contributor

Each Contributor shall receive an ACADEMIC CERTIFICATE as the copyright of the Contribution and 01 complimentary eBook copy of the Work in which the Contribution appears.