SecOBig: Security-Preserving Operations on Big Data

自从爱德华·斯诺登（Edward Snowden）揭露了美国国家安全局（NSA）和其他机构大量滥用数据以来，很明显，每一个关心数据隐私的个人和公司都必须采取措施保护数据。对于云存储和云计算场景中的外包数据，以及通过第三方（如Amazon的Elastic MapReduce）处理大数据时，更是如此。标准的密码学手段，如加密一般在这里不起作用，因为加密的本质，打乱所有合理的信息，数据的语义是隐藏的，不能被第三方使用来执行操作；为操作解密数据的选项将违背保护数据不受服务提供者侵犯的思想。为了协调安全需求和外包计算的能力，我们需要与期望操作兼容的密码学。2009年，IBM的研究人员宣布了一项密码学上的突破性成果，他们能够构建完全同态的加密方案，从而允许这种操作。然而，对于完全同态加密对大型数据集的适用性知之甚少。本研究项目的目标是提供支持安全大数据操作的加密解决方案。为了能够专注于这里的加密挑战，但仍然为处理大数据的不同架构提供有意义的解决方案，我们选择MapReduce框架作为我们构建的抽象层。因此，该项目的总体目标是使加密结构（如完全同态加密）适合外包大数据的需求，并将加密解决方案合并到MapReduce框架中。

Since Edward Snowden's disclosures of massive abuse of huge amounts of data by NSA and other agencies, it is evident that every individual and every company which cares about the privacy of their data has to take measures to protect the data. This is even more true for outsourced data in cloud storage and cloud computing scenarios, and when handling big data through third parties such as via Amazon's Elastic MapReduce. Standard cryptographic means such as encryption in general do not work here because by the very nature of encryption, scrambling all reasonable information, the semantics of the data are hidden and cannot be used by third parties to perform operations; the option of decrypting the data for the operations would violate the idea of protecting the data from the service provider.To reconcile the need for security with the ability to outsource computations we thus need cryptography which is compatible with the desired operations. In 2009 researchers from IBM announced a breakthrough result in cryptography by being able to build fully homomorphic encryption schemes which would allow such operations. However, little is known about the applicability of fully homomorphic encryption to large data sets. The goal of this research project is to provide cryptographic solutions which support operations on secured big data. To be able to focus on the cryptographic challenges here, but still providemeaningful solutions for different architectures to process big data, we choose the MapReduce framework as an abstract layer on which we base our constructions on. Hence, the overall goal of the project is to make cryptographic constructions such as fully homomorphic encryption fit the requirements of outsourced big data, and to incorporate the cryptographic solutions into the MapReduce framework.