About the Book
Offering a systematic exploration of blockchain networks from both technical and analytical viewpoints, this book introduces the core structures that underpin blockchain systems, transactions, addresses, and smart contracts and explains how these can be modeled, visualized, and analyzed using modern data science methods. Bridging computer science, finance, and statistics, it integrates algorithmic reasoning with economic intuition to study decentralization, risk, and trust in digital economies. Through examples drawn from Bitcoin, Ethereum, Ripple, Monero, Zcash, IOTA, and DeFi, readers learn how blockchain data can be transformed into graph and temporal models for fraud detection, systemic risk analysis, and network behavior prediction. Featuring clear explanations, illustrative figures, and Solidity code, this volume serves as an essential reference for students, researchers, and practitioners in finance, data science, statistics, machine learning, and distributed systems.
Table of Contents:
1. Money and cryptocurrencies; 2. Bitcoin: the first blockchain; 3. Ethereum: the world computer; 4. Solidity coding for Ethereum; 5. Ripple: the currency exchange; 6. Privacy coins; 7. Blockchain – next generation; 8. Decentralized finance; 9. Blockchain transaction networks; 10. Analyzing blockchain entities: clustering, mixing, and centrality; 11. Privacy and security on blockchain; 12. E-crime on blockchains; 13. Temporal analysis; 14. Conclusion; References; Index.
About the Author :
Cüneyt Gürcan Akçora is Associate Professor of Finance with a joint appointment in Computer Science at the University of Central Florida in Orlando. He is also a member of the university's AI Institute. His research focuses on data science for blockchains, integrating graph machine learning, temporal modeling, and network theory to study risk, fraud, and systemic behavior in decentralized finance. Murat Kantarcioglu is Professor and CCI Faculty Fellow in the Department of Computer Science at Virginia Tech. He is also a Faculty Associate at Harvard University's Data Privacy Lab. He is a fellow of the American Association for the Advancement of Science. His research focuses on AI for cybersecurity and cybersecurity for AI, integrating data science and blockchain technologies to design secure and efficient data systems. Yulia R. Gel is Professor of Statistics at Virginia Tech. She is a Fellow of the American Statistical Association and a recipient of the NSF Director's Award for Superior Accomplishment. Her research focuses on the mathematical and statistical foundations of data science, risk quantification, and topological and geometric methods for blockchain data analytics.
Review :
‘This book provides a lucid and concise introduction to blockchain technology and how it is revolutionizing the world of payments, investing and other areas of finance. The authors provide thorough introductions to the Bitcoin and Ethereum blockchains and take the reader up to the present with material on smart contracts, decentralized finance and emerging issues of privacy, cybersecurity, and crime. The book is suitable for university courses at both the undergraduate and graduate levels and should also be a valuable reference for practitioners.’ David L. Yermack, Leonard N. Stern School of Business, New York University
‘This coursebook offers a comprehensive and informative journey through blockchain technology-from the origins of digital money to advanced analytics on real blockchain data. Designed for students, practitioners, and researchers alike, the book bridges theory and practice with detailed explanations of Bitcoin, Ethereum and smart contracts, privacy-preserving systems, decentralized finance (DeFi) and DAOs, and algorithmic graph-based data analysis. Its unique combination of fundamental concepts, data structures, and algorithms make readers able not only to understand how blockchain systems work, but also to analyze and extract insights from their complex networks. With structured chapters, intuitive roadmaps, and self-assessment questions, this volume serves equally well as a course textbook and a standalone reference for independent study. A definitive resource for anyone serious about mastering blockchain within a data science framework.’ Elisa Bertino, Purdue University
