I-Corps: Lightweight Multi-Party Computations with Purpose Control

这个I-Corps项目的商业潜力是提供一个计算平台，方便多个实体进行交易，其中使用不同利益相关者拥有的数据，但不向包括平台在内的任何人披露。由此产生的交易将使各实体能够作出知情的决定，不仅从一批潜在的伙伴中进行选择，而且探索从其潜在的伙伴关系中创造价值的途径。该平台消除了失去数据所有权的任何可能性以及交易中对数据的任何误用/滥用。因此，它将激励不同实体之间的伙伴关系，从而提高价值和推出新产品。它可以改变游戏规则，允许一系列企业创造新的产品/服务，特别是当这些企业相互补充时。 此外，该平台将允许向最终客户提供个性化服务，涉及不同的实体，他们可以在不交换数据的情况下进行协作。这个I-Corps项目在其计算平台中使用一套构建模块来执行相互商定的计算。每个构建块被设计为使用单个外部服务器（SES）来执行特定的算术或逻辑运算，其中服务器不了解输入。使用这些构建块的实体只学习计算的输出，而不是他们的合作者的输入。因此，使用这些构建块执行的计算为每个涉及的实体保留了输入机密性和数据所有权。存在实现所述功能中的一些的现有技术，但是它们使用多个外部服务器或计算密集型加密技术。这些需求极大地影响了性能开销和可伸缩性，这使得在实际应用中部署它们变得困难。相比之下，与现有技术相比，这种基于SES的构建块导致性能开销的大幅降低，并且易于扩展。

The commercial potential of this I-Corps project is to provide a computational platform that facilitates multiple entities to transact where data owned by different stakeholders is used but not disclosed to anyone, including the platform. The resulting transaction would allow entities to make informed decisions about not only choosing from a pool of potential partners but also explore avenues to generate value from their potential partnership(s). This platform eliminates any possibility of losing ownership of data as well as any misuse/abuse of data in transactions. Consequently, it would motivate partnerships among disparate entities, leading to value enhancements and new products. It can be a game changer in allowing a range of businesses to create new products/services, especially when such businesses are complimentary to each other. Moreover, this platform would allow personalized service deliveries to end customers, involving different entities, who can collaborate without exchanging data.This I-Corps project uses a suite of building blocks within its computational platform to perform mutually-agreed computations. Each building block is designed to perform a specific arithmetic or a logical operation using a single external server (SES), wherein the server learns nothing about the inputs. The entities using these building blocks learn only the outputs of the computation but not their collaborators' inputs. Thus, computations executed using these building blocks preserve input confidentiality and data ownership for every involved entity. There are existing technologies that achieve some of the stated functionalities but they either use multiple external servers or computationally intensive cryptographic techniques. These requirements substantially affect the performance overhead and scalability, which make it difficult to deploy them in real-world applications. In contrast, this SES-based building blocks lead to substantial reductions in performance overhead as compared to the existing technologies and are easily scalable.