Lecture Notes in Networks and Systems1618 The 6th Joint International Conference on AI, Big Data Blockchain (AIBB 2025)

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Bol Security threat detection, fraud prevention and privacy-preserving applications 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.

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Security threat detection, fraud prevention and privacy-preserving applications 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.


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