TC: Small: Privacy-safe sharing of network data via secure queries (PSEQ)

这个项目将探索一个新的方向，以解决隐私/效用权衡的跟踪共享：安全查询下的原始跟踪其所有者？s控制。数据所有者发布查询语言和在线门户，允许研究人员提交对数据运行的查询集。仅允许对特定数据字段和特定上下文执行特定操作。此策略由提供程序艾德，并由语言解释器强制执行。解释器分析查询，运行那些被允许的查询，并将结果返回给研究人员。结果包括聚合信息，如计数，直方图，分布，而不是单个数据包。安全查询解决隐私/实用性权衡比消毒好得多。 隐私受到#64257的保护&;赋予数据所有者的细粒度控制，这允许检测许多被动攻击并最小化来自主动攻击的信息泄漏。未来的攻击向量可以通过在查询语言上添加新的约束来处理。安全查询还显示出向研究人员揭示更多数据的潜力，而不是通过清理。通过查询语言进行细粒度控制，可以处理应用程序头中的许多#64257;错误，甚至是敏感的应用程序内容，同时满足所有者的要求？的隐私问题。这项工作将调查网络跟踪数据的研究效用，以及已知和新的攻击与数据包ELD组合的关系，对这些ELD的操作，以及构成隐私风险的上下文。基于这些结果，该团队将开发一种安全的查询语言Trol，以及一种用于这种语言Patrol的解释器。Trol将支持网络研究所需的跟踪常见操作，而Patrol将禁止提供商艾德的构成隐私风险的查询和上下文？的隐私政策。语言和策略都可以由数据所有者扩展，以适应未来的发现。Trol和Patrol将部署在USC/ISI，并将在公开可用的、经过消毒的跟踪档案和合成生成的完整数据包跟踪上运行。这一部署将有助于测试Trol操作的表现力和隐私保护。这项工作还将在数据所有者中宣传这项工作，以推动从清理到通过安全查询保护痕迹的转变。

This project will explore a novel direction to address the privacy/ utility tradeoff of trace sharing: secure queries on original traces under their owner?s control. The data owner publishes a query language and an online portal, allowing researchers to submit sets of queries to be run on data. Only certain operations are allowed on certain data fields, and in specific contexts. This policy is specified by the provider and enforced by the language interpreter. The interpreter analyzes the queries, runs those that are permitted and returns the results to the researcher. The results consist of aggregate information such as counts, histograms, distributions and not of individual packets.Secure queries address privacy/utility tradeoff much better than sanitization. Privacy is protected by finer-grain control given to data owner, which permits detection of many passive attacks and minimization of information leakage from active attacks. Future attack vectors can be handled by adding new constraints on the query language. Secure queries also show a potential to reveal more data to researchers than it was possible with sanitization. Fine-grain control via query language enables processing of many fields in the application header, and even in sensitive application content, while satisfying the owner?s privacy concerns. This is likely to increase utility of public traces for application and security research.The work will investigate research utility of network trace data, and the relationship of known and novel attacks to combinations of packet fields, operations on those fields, and contexts that pose privacy risk. Based on these findings, the team will develop a secure query language Trol, and an interpreter for this language Patrol. Trol will support common operations on traces, needed for networking research, and Patrol will prohibit queries and contexts that pose a privacy risk as specified by the provider ?s privacy policy. Both the language and policies will be extensible by data owners to accommodate future discoveries. Trol and Patrol will be deployed at USC/ISI and will run on publicly available, sanitized trace archives and on synthetically generated, full packet traces. This deployment will help to test expressiveness and privacy protection of Trol operations. The work will also publicize the work among data owners, to motivate the shift from sanitization to protection of traces via secure queries.