Feedback and Optimisation for Well-behaved Anonymous Communication Networks

行为良好的匿名通信网络的反馈和优化

• 批准号: EP/V011294/1
• 负责人: Mohammad Tariq Ehsan Elahi
• 金额: $ 29.65万
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FV011294%2F1
• 关键词: Feedback; Optimisation; Well; behaved; Anonymous

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.

匿名通信网络（ACN），例如Tor和Mix Networks，可以保护我们敏感的通信元数据，例如我们与谁交谈，我们聊天的频率和多长时间。该元数据对隐私敏感是敏感的，因为它可以用来揭示可能隐藏的秘密，即使使用端到端加密也是如此。自从关于州级批量监视的雪登（Snowden）揭示以来，对互联网上的沟通隐私的主流兴趣不断增长，因此该项目是及时的。但是，要部署ACN是一个挑战，因为很难调整与实际实现的隐私水平相匹配的系统参数。这是由于ACNSIS对环境条件和用户行为严重影响的ACNSIS的隐私，安全性和性能。例如，通常认为当它们流过网络时，它们不会被碎片分散成较小的碎片。但是，现实是出于绩效原因，通常会分解消息。同样，假设用户活动持续存在，但是，用户倾向于全天具有爆发和平静的昼夜活动周期。为了解决这种当前情况，该项目旨在弥合基本差距，并提供一组框架和一组方法，以测量现实环境中的ACN，并在现实环境中进行测量，分析和调整ACN。它通过追求三个目标来做到这一点：1。映射与调整：新的分析，以揭示和形式化抽象安全参数与现实世界网络测量之间的关系，以最佳调整ACN。 2.反馈：使用反馈循环研究新颖的ACN设计，以提供在运行时自动调整安全参数的能力。3。用例验证：在针对性的电子邮件，Web浏览和IoT数据收集系统的有针对性的用例中进行评估，以验证自动调整方法。一种常见的发生激发了对该项目的需求。让我们考虑一个希望提供用户匿名性作为市场差异化的电子邮件提供商。指的是电子邮件提供的混音网络文献中的最新技术，非专家很难推理如何正确参数为电子邮件提供商的特定用户群来正确参数混合网络。映射和调整是丢失的成分阻止部署。鉴于在启动时进行了调整的ACN，可以使用反馈来自动设置并调整运行时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需要成为ACN设计的专家，也需要成为手动调整所需的抽象隐私指标。本项目将利用混合网络设计和保密网络数据收集的最新进步，这是我们可以扩展和增强的构建基础的基础。由此产生的值得信赖的智能和自适应ACN的持久积极影响将增加采用，从而为英国和全球公众提供强大的隐私。开发的技术，数据集和工具将开源，并将促进英国隐私技术市场。