CAREER: Measurement, Analysis, and Novel Applications of Blockchains

职业：区块链的测量、分析和新颖应用

• 批准号: 1651938
• 负责人: Arvind Narayanan
• 金额: $ 58.56万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-02-15 至 2022-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1651938&HistoricalAwards=false
• 关键词: CAREER; Measurement; Analysis; Novel; Applications

This research seeks to develop the science of blockchains. A blockchain is a distributed append-only database containing cryptographically linked records. The technology is the basis of cryptocurrencies (e.g., bitcoin). Principled methods for analyzing blockchain data will be developed in order to answer key questions about the economics, security, privacy, and anonymity of cryptocurrencies. The project envisions blockchains as the pillar of a new breed of decentralized applications and Internet security mechanisms. The project will develop a new open-source blockchain analysis tool, BlockSci, and use it to answer research questions including: How should we model cryptocurrency participants? How well do decentralized markets work, and how do they fail? How private are cryptocurrencies in practice? Can blockchains serve as the foundation for a secure, decentralized Internet? The research outputs of the project will be integrated into Princeton's Massive Online Open Course on cryptocurrencies, student projects, and a new course on the economics of security. The project will inform the cryptocurrency industry and developer community through conferences and release of open-source software.This project will combine computer science research on cryptocurrencies with cutting-edge techniques from game theory and mechanism design. The project could validate the applicability of powerful machine learning methods, including spectral graph analysis, to the rich data in blockchains. The system design and deployment component will contribute to important ongoing debates on the different approaches to scaling of big data analytics techniques. The PI will continue his engagement with policy makers and regulators to ensure that government agencies are informed by the results of this project.

这项研究旨在发展区块链科学。区块链是一个分布式的仅附加数据库，包含加密链接的记录。该技术是加密货币的基础（例如，比特币）。将开发分析区块链数据的原则性方法，以回答有关加密货币的经济性、安全性、隐私性和匿名性的关键问题。该项目将区块链视为新型分散应用程序和互联网安全机制的支柱。该项目将开发一个新的开源区块链分析工具BlockSci，并使用它来回答研究问题，包括：我们应该如何对加密货币参与者建模？去中心化的市场运作得如何，它们是如何失败的？加密货币在实践中有多私密？区块链可以作为安全、去中心化互联网的基础吗？该项目的研究成果将被整合到普林斯顿大学关于加密货币的大规模在线开放课程、学生项目和关于安全经济学的新课程中。该项目将通过会议和开源软件的发布向加密货币行业和开发者社区提供信息。该项目将联合收割机将加密货币的计算机科学研究与博弈论和机制设计的尖端技术相结合。该项目可以验证强大的机器学习方法（包括频谱图分析）对区块链中丰富数据的适用性。系统设计和部署部分将有助于正在进行的关于大数据分析技术扩展的不同方法的重要辩论。PI将继续与政策制定者和监管机构合作，以确保政府机构了解该项目的结果。

项目成果

Resurrecting Address Clustering in Bitcoin

• DOI: 10.1007/978-3-031-18283-9_19
• 发表时间: 2021-07
• 期刊: Journal of Biogeography
• 影响因子: 3.9
• 作者: Malte Möser;Arvind Narayanan

When the cookie meets the blockchain: Privacy risks of web payments via cryptocurrencies

• DOI: 10.1515/popets-2018-0038
• 发表时间: 2017-08
• 期刊: Proceedings on Privacy Enhancing Technologies
• 作者: Steven Goldfeder;Harry A. Kalodner;D. Reisman;Arvind Narayanan

Zero-Knowledge Contingent Payments Revisited: Attacks and Payments for Services

• DOI: 10.1145/3133956.3134060
• 发表时间: 2017-10
• 期刊: Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security
• 作者: Matteo Campanelli;R. Gennaro;Steven Goldfeder;Luca Nizzardo

BlockSci: Design and applications of a blockchain analysis platform

• 发表时间: 2017-09
• 作者: Harry A. Kalodner;Steven Goldfeder;Alishah Chator;Malte Möser;Arvind Narayanan