CiC: FRCC: Cloud Storage with Minimal Trust

这个项目提出了一个问题：如何在最小信任假设下构建云存储服务？该项目旨在设计、实现和评估一个实用的、具体的系统，该系统允许客户使用Azure和S3等云存储提供商，但客户不必信任提供商，也就是说，假设提供商总是正确运行。当然，减少假设通常是好的，但这样做与云存储特别相关：出于经济和运营原因，数据越来越多地迁移到存储服务提供商（ssp），然而ssp是复杂的黑盒子，可能会遇到软件错误、相关制造缺陷、错误配置的服务器、操作错误、恶意内部人员、破产、火灾等。由于这些原因，该项目正在构建一个名为Padova的系统，该系统可以容忍SSP中所有服务器失败的情况，这些失败包括恶意、错误或不太可能的不幸行为。该方法是在客户端强制执行合理的更新顺序；这为安全性提供了基础，并允许客户机从系统、客户机或服务器中的任何节点收集更新，这反过来又有助于提高活动性和可用性。Padova消除了对安全性的信任，并最小化了对活动性和可用性的信任。该项目使云存储对现有客户来说更加安全，并刺激云存储的进一步采用。这意味着更多的人为计算支付更少的费用，从而在整个计算生态系统中产生有益的影响。教育方面的好处包括研究生和本科生指导，后者通过德州大学的图灵学者计划培养特别有才华的本科生。

This project asks: how can one build a cloud storage service under minimal trust assumptions? The project aims to design, implement, and evaluate a practical, concrete system that allows clients to use cloud storage providers like Azure and S3 -- but without the clients having to trust, that is assume, that the providers always operate correctly. Of course, reducing assumptions is generically good, but doing so is particularly relevant to cloud storage: for economic and operational reasons, data is increasingly migrating to storage service providers (SSPs), yet SSPs are complex black boxes that can experience software bugs, correlated manufacturing defects, misconfigured servers, operator error, malicious insiders, bankruptcy, fires, and more. For these reasons, the project is building a system, called Padova, that tolerates scenarios in which all servers in the SSP fail, and the failures include malicious, buggy, or improbably unlucky behaviors. The approach is enforce a sensible ordering of updates at the client; this provides the foundation for safety and allows a client to gather updates from any node in the system, client or server, which in turn contributes to liveness and availability. Padova eliminates trust for safety and minimizes trust for liveness and availability.This project makes cloud storage safer for existing customers and spur further adoption of cloud storage. This means more people paying less for computing, producing beneficial effects throughout the computational ecosystem. The educational benefits include graduate and undergraduate mentoring, the latter through UT's Turing Scholars program, which cultivates particularly talented undergraduates.