The 6th Joint International Conference on AI, Big Data and Blockchain (AIBB 2025) (Lecture Notes in Networks and Systems, 1618)

This book brings together peer-reviewed research contributions exploring cutting-edge developments in AI, big data, and blockchain—fields that are transforming industries today. Written by leading experts, the chapters showcase advances in:

• AI methodologies and modelling—including machine learning and deep neural networks
• Big data analytics to uncover hidden patterns and insights
• Blockchain-based data management methods, privacy-preserving architecture and trust-enhancing systems
• Security threat detection, fraud prevention and privacy-preserving applications

With applications ranging from industrial-scale systems to real-world, high-stakes environments, this book serves as an essential resource for:

• Researchers exploring next-generation AI, blockchain and data science approaches
• Practitioners and developers implementing enterprise-scale solutions
• Industry professionals and policy-makers seeking best practices in secure, transparent and accountable computing

This book offers both theoretical depth and applied relevance, making it a valuable reference to guide innovation in data-driven and decentralised systems.

This book brings together peer-reviewed research contributions exploring cutting-edge developments in AI, big data, and blockchain—fields that are transforming industries today. Written by leading experts, the chapters showcase advances in:

• AI methodologies and modelling—including machine learning and deep neural networks
• Big data analytics to uncover hidden patterns and insights
• Blockchain-based data management methods, privacy-preserving architecture and trust-enhancing systems
• Security threat detection, fraud prevention and privacy-preserving applications

With applications ranging from industrial-scale systems to real-world, high-stakes environments, this book serves as an essential resource for:

• Researchers exploring next-generation AI, blockchain and data science approaches
• Practitioners and developers implementing enterprise-scale solutions
• Industry professionals and policy-makers seeking best practices in secure, transparent and accountable computing

This book offers both theoretical depth and applied relevance, making it a valuable reference to guide innovation in data-driven and decentralised systems.