InTrans: Modular Security on an Open Cloud

该项目探索了两种工具组合带来的有趣的可能性：一种是加密软件，只要机器处于隔离状态，就将任何计算任务分配到多台机器上，并提供强大的安全保证；另一种是多提供商云数据中心，它向任何租户提供租用由不同组织管理的多台隔离机器的能力。该项目的创新之处在于优化加密安全多方计算(MPC)，以用于多提供商数据中心，利用此类数据中心已经提供的安全属性。该项目的影响是开源软件包，它们为采用多提供商方法的云数据中心(如大规模开放云(MOC))提供了引人注目的应用程序。本田研究院和红帽这两个行业合作伙伴对此INTRANS项目的研究非常感兴趣，它建立在模块化方法到云安全前沿项目的基础上。更详细地说，这个跨学科的项目包括三组跨越密码学和分布式系统的任务。首先，调查人员探索机会，针对我们观察到的行业合作伙伴和其他人对其感兴趣的特定场景，改进和优化MPC的算法设计。其次，调查人员调整和优化系统软件和现有的MOC工具，以改进MPC的联网和分布式计算步骤。第三，调查人员对交通部的安全相关系统进行通用可组合性(UC)安全分析，以确定对MPC的贡献程度。这三项任务是相互依赖的：例如，MOC的UC模型可以提供对将软件与部分受信任的硬件相结合的新MPC算法设计的见解，并验证云是否满足MPC要求的前提条件(如节点之间的隔离)。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project explores the intriguing possibilities that result from the combination of two tools: cryptographic software that distributes any computing task over several machines with strong security guarantees as long as the machines are isolated, and a multi-provider cloud datacenter that offers to any tenant the ability to rent multiple isolated machines that are administered by different organizations. The project's novelties are to optimize cryptographically secure multi-party computation (MPC) for use in a multi-provider datacenter, leveraging the security properties already provided by such datacenters. The project's impacts are open-source software packages that provide a compelling application for cloud datacenters like the Mass Open Cloud (MOC) that adopt a multi provider approach. The research in this InTrans project is of strong interest to two industrial partners, Honda Research Institutes and Red Hat, and it builds on top of the work performed in the Modular Approach to Cloud Security Frontier project.In more detail, this cross-disciplinary project encompasses three sets of tasks that span cryptography and distributed systems. First, the investigators explore opportunities to improve and optimize the algorithmic design of MPC toward specific scenarios for which we have observed large interest by our industry partners and others. Second, the investigators adapt and optimize system software and existing MOC tools to improve MPC's networking and distributed computing steps. Third, the investigators perform a universal composability (UC) security analysis of the MOC's security-relevant systems in order to determine the extent to which can contribute toward MPC. These three tasks are co-dependent: for instance, a UC model of the MOC can provide insights into the design of new MPC algorithms that combine software with partially trusted hardware and to validate whether the cloud meets the pre-conditions required by MPC (such as isolation between nodes).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.