EAGER: Privacy-preserving measurements of the Tor network to improve performance and anonymity

EAGER：Tor 网络的隐私保护措施，以提高性能和匿名性

• 批准号: 0959138
• 负责人: Roger Dingledine
• 金额: $ 30万
• 依托单位: Drexel University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0959138&HistoricalAwards=false
• 关键词: EAGER; Privacy; preserving; measurements; Tor

As the Tor network has grown since 2003 to almost 2000 volunteer relays, the anonymity that it can provide has grown too. This project is measuring Tor's network characteristics and usage, laying the foundation for evaluating its anonymity and improving performance. The project is addressing three components of this challenge. First, it invents new algorithms for collecting Tor network load and usage data safely, including new metrics to ensure that collected data doesn't harm privacy too much yet is still useful for research. Second, it collects and make available aggregated data about the live Tor network over time, and design and deploy new tools to manipulate and understand this data. Third, it identifies which measurements are necessary to support the wider performance and anonymity research questions, do the measurements, and feed the results into the anonymity community's ongoing research projects. Research Activity 1: Directory and network data. Analyze patterns in directory authority opinions to tune them for better network anonymity and performance, and then track long-term characteristics like churn rate so researchers can simulate design changes. Research Activity 2: Performance data. Design and perform measurements to better understand why the Tor network has high (and highly variable) latency. Early investigations show that queuing inside Tor's relays contributes to this latency. Discovering what exactly is wrong with Tor's congestion control mechanisms will allow designers to learn whether proposed improvements actually help. The project will also investigate other theories of how to improve performance, such as: a) Tor's round-robin scheduling approach should prioritize interactive traffic over bulk traffic; b) incentive systems could encourage users to relay traffic; c) Tor's path selection algorithms should load balance better over the relays; and d) clients should handle variable latency and connection failures by dynamically adapting to observed network quality.

自2003年以来，Tor网络已经发展到近2000名志愿者中继，它所能提供的匿名性也在增长。该项目测量Tor的网络特性和使用情况，为评估其匿名性和提高性能奠定基础。该项目正在解决这一挑战的三个组成部分。首先，它发明了安全收集Tor网络负载和使用数据的新算法，包括新的指标，以确保收集的数据不会过多地损害隐私，但仍对研究有用。其次，随着时间的推移，它收集并提供实时Tor网络的汇总数据，并设计和部署新的工具来操纵和理解这些数据。第三，它确定哪些测量是必要的，以支持更广泛的性能和匿名研究问题，进行测量，并将结果提供给匿名社区正在进行的研究项目。研究活动1：目录和网络数据。分析目录权威意见中的模式，以调整它们以获得更好的网络匿名性和性能，然后跟踪长期特征，如流失率，以便研究人员可以模拟设计更改。研究活动2：性能数据。设计和执行测量，以更好地理解为什么Tor网络具有高（和高度可变）延迟。早期的调查表明，Tor中继中的排队导致了这种延迟。发现Tor的拥塞控制机制到底有什么问题，将使设计者了解所提出的改进是否真的有帮助。该项目还将研究如何提高性能的其他理论，例如：a) Tor的循环调度方法应该优先考虑交互式流量而不是批量流量；B)激励机制可以鼓励用户转发流量；c) Tor的路径选择算法应该在中继上更好地进行负载平衡；d)客户端应该通过动态适应观察到的网络质量来处理可变延迟和连接故障。