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来解决跟踪共享的隐私/效用权衡：在其所有者下对原始跟踪进行安全查询？年代的控制。数据所有者发布了一种查询语言和一个在线门户，允许研究人员提交一组查询，以便在数据上运行。只允许对某些数据进行某些操作。Elds，并在指定&amp；#64257；c上下文。这个政策是特别的&amp；#64257；由提供者编写并由语言解释器执行。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。结果包括计数、直方图、分布等汇总信息，而不是单个数据包。安全查询处理隐私/实用程序的权衡比清理要好得多。隐私受到&amp；#64257；为数据所有者提供了自粒度控制，允许检测许多被动攻击，并将主动攻击的信息泄漏最小化。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。安全查询也显示出向研究人员揭示更多数据的潜力，而不是消毒。通过查询语言进行细粒度控制，可以处理许多&amp；#64257；字段在应用程序头，甚至在敏感的应用程序内容，同时满足所有者？美国的隐私问题。这可能会增加公共跟踪对应用程序和安全研究的效用。这项工作将调查网络跟踪数据的研究效用，以及已知和新攻击与数据包组合的关系。字段，对那些&amp；#64257；字段，以及构成隐私风险的上下文。基于这些&amp；#64257；最后，该团队将开发一种安全的查询语言Trol，并为该语言开发一个解释器。Trol将支持网络研究所需的常见跟踪操作，而Patrol将禁止构成隐私风险的查询和上下文。由供应商提供？S隐私政策。数据所有者可以对语言和策略进行扩展，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、完整的数据包跟踪上运行。此部署将有助于测试Trol操作的表达性和隐私保护。这项工作还将在数据所有者中宣传这项工作，通过安全查询推动从清理到保护痕迹的转变。

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.