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Machine Learning and Blockchain – Challenges, Future Trends and Sustainable Technologies
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Editors: Keshav Kaushik, Rewa Sharma, Ayodeji Olalekan Salau

Machine Learning and Blockchain – Challenges, Future Trends and Sustainable Technologies

eBook: US $69 Special Offer (PDF + Printed Copy): US $125
Printed Copy: US $90
Library License: US $276
ISBN: 978-981-5324-22-8 (Print)
ISBN: 978-981-5324-21-1 (Online)
Year of Publication: 2026
DOI: 10.2174/97898153242111260101
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Introduction

With contributions from leading researchers and industry experts, this book examines cutting-edge applications, integration models, and sustainable solutions across sectors including finance, agriculture, healthcare, IoT, and smart cities.

Chapters cover blockchain-enabled fintech operations, fraud detection, deep learning–driven intrusion detection, AI-enhanced smart contracts, and data-driven healthcare innovations. Case studies, methodologies, and future-oriented insights demonstrate how these technologies can foster secure, efficient, and sustainable ecosystems. By bridging theoretical foundations with practical implementations, this book offers readers a roadmap to navigate the opportunities and challenges shaping the next generation of intelligent, blockchain-powered systems.

Key Features

  • - Integrates blockchain with machine learning for real-world applications.
  • - Applies advanced analytics, automation, and AI models to enhance blockchain ecosystems.
  • - Develops secure solutions in fintech, agriculture, healthcare, IoT, and smart cities.
  • - Evaluates case studies and frameworks addressing challenges and vulnerabilities.
  • - Explores sustainable, future-ready trends shaping intelligent systems.

Readership:

For researchers, graduate students, and academicians in computer science, IT, and data science, as well as industry practitioners, fintech innovators, and blockchain developers.


eBook: US $69 Special Offer: US $125 Printed Copy: US $90 Library License: US $276

Preface

Machine Learning and Blockchain-Challenges, Future Trends and Sustainable Technologies (MLB) by Bentham Science is a brainchild of Keshav Kaushik, Rewa Sharma, and Ayodeji Olalekan Salau. The goal of this book is to make it easier for academics and prospective readers to grasp blockchain technology and machine learning. They will be able to practice and gain expertise with ML techniques thanks to this book. The book will provide readers with a thorough grasp of the cutting-edge technologies around blockchain, artificial intelligence, and machine learning. These technologies have the ability to collect and process enormous amounts of data from the real world. The edited book will be set up with distinct chapters to provide readers with maximum readability, flexibility, and adaptability. We are very grateful to all of our co-authors for sharing their expertise and experience; they are all authorities in their fields. This book is an attempt to gather their thoughts and share them with the world in the format of chapters. This book offers insights into AI, FinTech, Deep Learning, Blockchain, Machine Learning, and Blockchain applications. Academicians, industry professionals, researchers, undergrads, and grads will all find the book useful. We acknowledge Bentham Science Publishers and all of the authors of this book for their cooperative efforts.

Keshav Kaushik
Center for Cyber Security and Cryptology
Sharda School of Computer Science & Engineering
Sharda University, Greater Noida
India

Rewa Sharma
J.C Bose University of Science and Technology
YMCA, Faridabad, India

&

Ayodeji Olalekan Salau
Department of Electrical and Electronics
and Computer Engineering, Afe Babalola University
Ado Ekiti, Nigeria