Feedback and Optimisation for Well-behaved Anonymous Communication Networks

匿名通信网络(ACNS)，如Tor和Mix网络，保护我们的敏感通信元数据，如我们与谁交谈，我们聊天的频率和时间。这种元数据是隐私敏感的，因为它可以用来泄露原本可能被隐藏的秘密，即使在使用端到端加密时也是如此。这个项目很及时，因为自斯诺登事件以来，人们对互联网通信隐私的主流兴趣与日俱增--斯诺登揭露了国家层面的大规模监控。然而，对于ACNS的部署来说，这是一个挑战，因为很难调整系统参数以匹配实际实现的隐私水平。这是因为ACNS的隐私、安全和性能受到环境条件和用户行为的严重影响。例如，人们经常假设消息在网络上流动时没有分段-被分成更小的部分-。然而，现实情况是，出于性能原因，消息经常被分解。类似地，假设用户的活动水平是恒定的，然而，用户倾向于在整个DAY期间具有突发和间歇的日常活动周期。为了弥补这一现状，本项目旨在弥合根本差距，并提供一个框架和一套方法来在现实环境中测量、分析和调整ACNS。它通过追求三个目标来做到这一点：1.映射和调整：新的分析，以发现和正规化抽象安全参数和现实世界网络测量之间的关系，以期以最佳方式调整ACN。2.反馈：研究具有反馈环路的新型ACN设计，这些环路能够在运行时自动调整安全参数。用例验证：在电子邮件、Web浏览和物联网数据收集系统的目标使用案例中进行评估，以验证自动调整方法。一种常见的情况激发了对此项目的需求。让我们考虑一家希望提供用户匿名性作为市场差异化优势的电子邮件提供商。参考电子邮件安全MIX网络文献中的最新技术，非专家很难推理如何针对电子邮件提供商的特定用户群正确地设置MIX网络的参数。映射和调优是阻碍部署的缺失因素。在启动时给定调谐的ACN，可以使用反馈来在运行时自动设置和调整电子邮件匿名服务所需的安全参数。提供商或其系统管理员都不需要成为ACN设计方面的专家，也不需要具备手动调整所需的抽象隐私指标。该项目将利用MIX网络设计和隐私保护网络数据收集方面的最新进展，作为我们可以扩展和增强的构建块的基础。由此产生的值得信赖、智能和自适应的ACNS的持久积极影响将是更多的人采用ACNS，从而为英国和全球公众提供强大的隐私保护。开发的技术、数据集和工具将是开源的，将推动英国隐私技术市场的发展。

Anonymous communication networks (ACNs), like Tor and mix networks, protect our sensitive communication meta-data, such as whom we talk with, how often we chat and for how long. This meta-data is privacy sensitive since it can be used to reveal secrets that might otherwise be hidden, even when end-to-end encryption is used. This project is timely since mainstream interest in communication privacy on the Internet has grown since the Snowden-revelations about state-level mass surveillance. However, it is a challenge for ACNs to be deployed since it is hard to tune system parameters that matches the actual realised level of privacy.This is due to the fact that the privacy, security, and performance of ACNsis critically impacted by environmental conditions and user behaviour. For example, it is often assumed thatmessages are not fragmented---broken up into smaller pieces---as they flow over the network. However, the reality is that messages are routinely broken up for performance reasons. Similarly, it is assumed that there is a constant level of user activity, however, users tend to have diurnal activity cycles with bursts and lulls throughout the day.To remedy this current situation, this project aims to bridge the fundamental gaps and provides a framework and a set of methodologies to measure, analyse, and tune ACNs in realistic settings. It does this by pursuing three objectives:1. Mapping & Tuning: New analysis to uncover and formalise relationships between abstract security parameters and real-world network measurements with the view to optimally tune the ACN. 2. Feedback: Investigate novel ACN designs with feedback loops that provide the ability to automatically tune security parameters at run time.3. Use-case validation: Evaluate in targeted use-cases of email, web-browsing, and IoT data collection systems to validate the automated tuning methodology.A common occurrence motivates the need for this project. Let us consider an email provider desiring to provide user anonymity as a market differentiator. Referring to the state-of-the-art in the email-securing mix networks literature it is difficult for the non-expert to reason how to correctly parametrise the mix network for the email provider's particular user base. Mapping & Tuning are the missing ingredients holding back deployment. Given a tuned ACN at start-up time, Feedback can be employed to automatically set and adjust the security parameters necessary for the email anonymity service at run time. The provider nor its system administrator needs to become expert in ACN design nor the abstract privacy metrics necessary for manual tuning.This project will leverage recent advancements in the design of mix networks and privacy-preserving network data collection as the basis of our building blocks from which we can extend and enhance. The lasting positive impact of the resultant trustworthy intelligent and adaptive ACNs will be increased adoption and therefore robust privacy for the UK and global public. The technology, data-sets, and tooling developed will open-sourced and will be a boost to the UK privacy technologies marketplace.