SaTC: CORE: Small: Collaborative: A Broad Treatment of Privacy in Blockchains

区块链为安全、去中心化的信息共享提供了新的视角，预计将成为未来的技术。区块链最初是作为加密货币的基础机制引入的，用于保护金融交易，而无需中央可信方。如今，区块链也因其在从身份管理到健康数据记录等各种背景下的潜在优势而受到认可。然而，尽管区块链是一个很有前途的工具，但发布在区块链上的数据是公开的，并且是永久捕获的，因此如果不考虑隐私问题，用户的隐私可能会受到大规模侵犯。该项目的目标是为区块链和隐私保护工具中的隐私开发一个正式模型。该项目开发了一个框架，该框架在反映互联网对抗能力的威胁模型下捕获交易，数据块和挖掘过程的隐私要求（即，可组合安全性）。在这个框架的基础上，研究人员研究了现有区块链支付系统的新隐私保护机制，以及设计具有内置隐私属性的新的基于区块链的支付系统，这些支付系统不需要可信的设置。 接下来，研究人员调查了新的隐私要求，例如隐藏矿工的身份，这在挖掘区块可能意味着对区块中包含的信息的认可的情况下是相关的。最后，研究人员开发了一些技术来保证问责制，即使是在隐私保护的环境中，只要没有检测到预先指定的不良行为，隐私就应该得到保护。

Blockchains provide a new perspective on secure, decentralized information sharing and are projected to be the technology of the future. Blockchains were first introduced as the underlying mechanism of cryptocurrencies and are used to secure financial transactions without the need for a central trusted party. Today, blockchains are also recognized for their potential advantages in various contexts ranging from identity management to health data records. However, despite being such a promising tool, the data posted on a blockchain is public and immortally captured and thus the privacy of the users can be massively violated if privacy concerns are not taken into consideration. The goals of this project are to develop a formal model for privacy in blockchains and privacy-preserving tools.This project develops a framework that captures privacy requirements for transactions, data blocks and the mining process under a threat model that reflects the adversarial capabilities over the Internet (i.e., composable security). Building on this framework, the researchers investigate new privacy-preserving mechanisms for existing blockchain payment systems and the design of new blockchain-based payment systems with built-in privacy properties that do not require a trusted setup. Next, the researchers investigate new privacy requirements like hiding the identity of the miner which is relevant in scenarios where mining a block might signify the endorsement of the information included in the block. Finally, the researchers develop techniques to guarantee accountability even in a privacy-preserving setting where privacy should be preserved only so long as a pre-specified bad behavior is not detected.