Decentralized Collaborative Learning for Data Priv acy and Security

Master the future of secure technology with this essential guide, which delivers a practical, forward-looking blueprint for combining AI, blockchain, and advanced cryptography to build powerful, decentralized systems without compromising data privacy.

As AI systems grow more powerful and data more valuable, the tension between collaborative intelligence and individual privacy has never been more urgent. This book confronts this challenge head-on, offering a comprehensive and forward-looking exploration of how federated learning, blockchain technology, and advanced cryptographic techniques can be combined to build AI systems that are powerful and trustworthy. From foundational concepts in distributed machine learning and data sovereignty to cutting-edge topics such as zero-knowledge proofs, homomorphic encryption, and quantum-resistant privacy solutions, this book is structured to serve both learners and practitioners. The book moves deliberately from theory to practice, establishing core principles before tackling complex architectures, consensus mechanisms, smart contract governance, and incentive models that make decentralized AI networks viable at scale. Real-world applications anchor the technical content throughout, with dedicated chapters examining privacy-preserving fraud detection in finance, blockchain-AI collaboration in healthcare, and intelligent infrastructure in smart cities and IoT ecosystems. Supported by case studies, architectural diagrams, and practical guidance on tools, it is an essential resource for anyone working at the intersection of AI, blockchain, and data privacy to shape the secure, decentralized intelligent systems of tomorrow.

Master the future of secure technology with this essential guide, which delivers a practical, forward-looking blueprint for combining AI, blockchain, and advanced cryptography to build powerful, decentralized systems without compromising data privacy.

Bipin Kumar Rai, PhD is a Professor in the Department of Computer Science and Engineering, Dayananda Sagar University, Bangalore. With more than 21 years of experience, he has published more than 70 research papers in international journals and conferences, seven books, and five patents. His interests include information security, machine learning, and blockchain.

Rupa Rani, PhD is an Assistant Professor in the Department of Computer Science and Engineering at Ajay Kumar Garg Engineering College, Ghaziabad, India. With over a decade of teaching experience, she has published more than 20 research papers in reputed international journals and conferences. Her research interests include data science, artificial intelligence, machine learning, and cyber security.

Chin-Shiuh Shieh, PhD is a Professor in the Department of Electronic Engineering at the National Kaohsiung University of Science and Technology, Kaohsiung. He has more than 200 publications to his credit, including books, chapters, and journal articles. His research interests include wireless networks and handover techniques.