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

许多组织和个人依靠云来存储数据和处理分析查询。但这些数据可能包含敏感信息。用户不仅希望在云上隐藏他们的数据，他们还可能希望隐藏对他们的数据的分析查询，这些查询的结果，以及来自云服务提供商的数据访问模式（可能会受到来自内部或第三方的影响）。SEAL使用安全加密方案加密数据，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，该框架允许指定不同级别的所需安全性。SEAL的设计特别探索了安全性和效率之间的权衡，为各种分析操作提供了具有不同可证明安全性和效率特性的解决方案。用户能够继续享受云计算所提供的好处，但现在不必担心丢失敏感信息，并且可以控制安全性和效率权衡。

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.