TWC: Medium: Collaborative: Seal: Secure Engine for AnaLytics - From Secure Similarity Search to Secure Data Analytics

许多组织和个人依赖云来存储他们的数据并处理他们的分析查询。但这类数据可能包含敏感信息。用户不仅想要在云上隐藏他们的数据，他们还可能想要向云服务提供商隐藏对其数据的分析查询、此类查询的结果和数据访问模式(可能会从内部或第三方泄露)。该研究设计并实现了SEAL，这是一个安全的引擎，用于对云上的大数据进行分析。Seal使用安全加密方案对数据进行加密，但通过构建元答案数据库的新方法支持分析操作。Seal是在一个安全框架内开发的，该框架允许指定所需的不同安全级别。SEAL的设计特别探讨了安全和效率之间的权衡，为各种分析操作提供了具有不同可证明的安全和效率特征的解决方案。用户可以继续享受云必须提供的好处，但现在无需担心丢失敏感信息，也无需控制安全和效率的权衡。

Many organizations and individuals rely on the cloud to store their data and process their analytical queries. But such data may contain sensitive information. Not only do users want to conceal their data on a cloud, they may also want to hide analytical queries over their data, results of such queries, and data access patterns from a cloud service provider (that may be compromised either from within or by a third party).This research designs and implements SEAL, a Secure Engine for AnaLytics over large data on a cloud. SEAL encrypts data using secure encryption schemes, but supports analytical operations through a new approach of building a meta-answer database. SEAL is developed within a security framework that allows specifying different levels of desired security. The design of SEAL in particular explores the tradeoff between security and efficiency, providing solutions with different provable security and efficiency features for a wide variety of analytical operations. Users are able to continue to enjoy the benefits a cloud has to offer, but now without the worry of losing sensitive information and with control over the security and efficiency tradeoff.