The 6th Joint International Conference on AI, Big Data and Blockchain (AIBB 2025) (eBook, PDF)
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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 ind...
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:
With applications ranging from industrial-scale systems to real-world, high-stakes environments, this book serves as an essential resource for:
This book offers both theoretical depth and applied relevance, making it a valuable reference to guide innovation in data-driven and decentralised systems.
- 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.
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