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 网络，可以保护我们敏感的通信元数据，例如我们与谁交谈、聊天的频率和时长。该元数据对隐私敏感，因为即使使用端到端加密，它也可用于揭示可能隐藏的秘密。该项目是及时的，因为自斯诺登揭露国家级大规模监控以来，主流对互联网通信隐私的兴趣不断增长。然而，ACN 的部署是一个挑战，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 ACN 的隐私、安全和性能严重受到环境条件和性能的影响。用户行为。例如，通常假设消息在网络上流动时不会被分段（被分解为更小的片段）。然而，现实情况是，由于性能原因，消息通常会被分解。同样，假设用户活动水平恒定，但是，用户往往有昼夜活动周期，全天都有爆发和间歇。为了弥补这种现状，该项目旨在弥合根本差距并提供一个框架以及一套在现实环境中测量、分析和调整 ACN 的方法。它通过追求三个目标来实现这一目标：1。映射和调整：新的分析揭示并形式化抽象安全参数与现实世界网络测量之间的关系，以优化 ACN 的调整。 2. 反馈：研究具有反馈循环的新颖 ACN 设计，该设计能够在运行时自动调整安全参数。3.用例验证：评估电子邮件、网络浏览和物联网数据收集系统的目标用例，以验证自动调优方法。一种常见的情况激发了对该项目的需求。让我们考虑一下一家电子邮件提供商希望为用户提供匿名性作为市场差异化因素。参考电子邮件安全混合网络文献中的最新技术，非专家很难推断出如何针对电子邮件提供商的特定用户群正确地参数化混合网络。映射和调整是阻碍部署的缺失因素。给定启动时调整的 ACN，反馈可用于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。提供商及其系统管理员都需要成为 ACN 设计方面的专家，也不需要成为手动调整所需的抽象隐私指标的专家。该项目将利用混合网络设计和隐私保护网络数据收集方面的最新进展，作为我们构建块的基础我们可以扩展和增强它。由此产生的值得信赖的智能和自适应 ACN 的持久积极影响将是增加采用率，从而为英国和全球公众提供强大的隐私保护。开发的技术、数据集和工具将开源，并将推动英国隐私技术市场的发展。