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Handbook of Blockchain Analytics [Kõva köide]

  • Formaat: Hardback, 1000 pages, kõrgus x laius: 235x155 mm, Approx. 1000 p., 1 Hardback
  • Sari: Springer Handbooks of Computational Statistics
  • Ilmumisaeg: 02-Oct-2025
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3031954173
  • ISBN-13: 9783031954177
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  • Formaat: Hardback, 1000 pages, kõrgus x laius: 235x155 mm, Approx. 1000 p., 1 Hardback
  • Sari: Springer Handbooks of Computational Statistics
  • Ilmumisaeg: 02-Oct-2025
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3031954173
  • ISBN-13: 9783031954177

This handbook delves into the multifaceted domain of blockchain technology and its applications, offering insights across technological, economic, and practical dimensions. It is divided into several parts, reflecting analysis techniques specific to different fields of application, including digital finance, security and supply chains, among others.

The book begins with a foundational exploration of blockchain technology, providing a comprehensive understanding of its core mechanisms. The analysis extends to cutting-edge topics such as Non-Fungible Tokens (NFTs) and visualization technologies, which reveal the dynamic interplay between digital assets and technological innovation.

Cryptocurrency liquidity and market dynamics are also examined, employing principles like Metcalfe's Law and Log-Periodic Power Laws to unravel complex market behaviors. Empirical studies shed light on volatility forecasting and the impact of sudden market jumps, enriching the predictive frameworks for cryptocurrency trading.

In the realm of blockchain analytics, advanced methodologies like process mining are applied to uncover patterns in blockchain applications, while network analytics provide tools for fraud detection and heuristic evaluation. Decision-making in blockchain transactions is explored through the lens of mempool dynamics, providing practical insights for optimizing blockchain operations.

The narrative extends to business applications, highlighting strategies for blockchain-driven development and the legal and financial implications of Distributed Ledger Technology (DLT). Blockchain’s transformative potential in healthcare is showcased, alongside a survey of federated learning frameworks that leverage blockchain for secure and decentralized machine learning.

Security remains a pivotal theme, with a focus on the role of blockchain in cybersecurity and compliance functions. The investigation addresses decentralized finance (DeFi) vulnerabilities through case studies on attacks, offering lessons to enhance system robustness. Finally, the text envisions a future where decentralized models democratize foundational technologies, and blockchain facilitates innovations in maritime supply chains, driving efficiency and transparency in global logistics.

This compilation serves as a gateway to understanding the theoretical and practical dimensions of blockchain, emphasizing its evolving role in reshaping industries and economic systems.

Introduction to Blockchain.- Consensus in Blockchain and Distributed
Ledger Systems.- Digital Assets in Blockchains.- Cryptoeconomics.- Blockchain
Analytics.- Blockchains and Finance.- Modern Applications.- The Blockchain
Ecosystem.
Cathy Yi-Hsuan Chen is a Professor at Adam Smith Business School at the University of Glasgow, UK and Senior Researcher in Institute Digital Assets, Academy of Economic Sciences, Bucharest.



Wolfgang Karl Härdle is the Ladislaus von Bortkiewicz Emeritus Professor of Statistics at the Humboldt-Universität zu Berlin, Germany and the Director of IDA, Institute Digital Assets, Academy of Economic Sciences, Bucharest, Romania and Yushan Scholar, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.



Henry Horng-Shing Lu is a Distinguished Professor in Kaohsiung Medical University, and National Yang Ming Chiao Tung University, Taiwan. He is the Dean of Biomedical Artificial Intelligence Academy in Kaohsiung Medical University. He is also an Adjunct Professor, Department of Statistics and Data Science, Cornell University, New York, USA.