[2410.10110] Mastering AI: Big Data, Deep Learning, and the Evolution of Large Language Models -- Blockchain and Applications
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Computer Science > Cryptography and Security

arXiv:2410.10110 (cs)
[Submitted on 14 Oct 2024 (v1), last revised 17 Dec 2024 (this version, v2)]

Title:Mastering AI: Big Data, Deep Learning, and the Evolution of Large Language Models -- Blockchain and Applications

Authors:Pohsun Feng, Ziqian Bi, Lawrence K.Q. Yan, Yizhu Wen, Benji Peng, Junyu Liu, Caitlyn Heqi Yin, Tianyang Wang, Keyu Chen, Sen Zhang, Ming Li, Jiawei Xu, Ming Liu, Xuanhe Pan, Jinlang Wang, Qian Niu
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Abstract:A detailed exploration of blockchain technology and its applications across various fields is provided, beginning with an introduction to cryptography fundamentals, including symmetric and asymmetric encryption, and their roles in ensuring security and trust within blockchain systems. The structure and mechanics of Bitcoin and Ethereum are then examined, covering topics such as proof-of-work, proof-of-stake, and smart contracts. Practical applications of blockchain in industries like decentralized finance (DeFi), supply chain management, and identity authentication are highlighted. The discussion also extends to consensus mechanisms and scalability challenges in blockchain, offering insights into emerging technologies like Layer 2 solutions and cross-chain interoperability. The current state of academic research on blockchain and its potential future developments are also addressed.
Comments: This book contains 241 pages and 5 figures
Subjects: Cryptography and Security (cs.CR)
Cite as: arXiv:2410.10110 [cs.CR]
  (or arXiv:2410.10110v2 [cs.CR] for this version)
  https://doi.org/10.48550/arXiv.2410.10110

Submission history

From: Ming Liu [view email]
[v1] Mon, 14 Oct 2024 02:56:36 UTC (219 KB)
[v2] Tue, 17 Dec 2024 05:03:42 UTC (215 KB)
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