4 research outputs found

    Using Open Stack for an Open Cloud Exchange(OCX)

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    We are developing a new public cloud, the Massachusetts Open Cloud (MOC) based on the model of an Open Cloud eXchange (OCX). We discuss in this paper the vision of an OCX and how we intend to realize it using the OpenStack open-source cloud platform in the MOC. A limited form of an OCX can be achieved today by layering new services on top of OpenStack. We have performed an analysis of OpenStack to determine the changes needed in order to fully realize the OCX model. We describe these proposed changes, which although significant and requiring broad community involvement will provide functionality of value to both existing single-provider clouds as well as future multi-provider ones

    HIL: designing an exokernel for the data center

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    We propose a new Exokernel-like layer to allow mutually untrusting physically deployed services to efficiently share the resources of a data center. We believe that such a layer offers not only efficiency gains, but may also enable new economic models, new applications, and new security-sensitive uses. A prototype (currently in active use) demonstrates that the proposed layer is viable, and can support a variety of existing provisioning tools and use cases.Partial support for this work was provided by the MassTech Collaborative Research Matching Grant Program, National Science Foundation awards 1347525 and 1149232 as well as the several commercial partners of the Massachusetts Open Cloud who may be found at http://www.massopencloud.or

    Enabling secure multi-party computation with FPGAs in the datacenter

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    Big data utilizes large amounts of processing resources requiring either greater efficiency or more selectivity. The collection and managing of such large pools of data also introduces more opportunities for compromised security and privacy, necessitating more attentive planning and mitigations. Multi-Party Computation (MPC) is a technique enabling confidential data from multiple sources to be processed securely, only revealing agreed-upon results. Currently, adoption is limited by the challenge of basing a complete system on available software libraries. Many libraries require expertise in cryptography, do not efficiently address the computation overhead of employing MPC, and leave deployment considerations to the user. In this work we consider the available MPC protocols, changes in computer hardware, and growth of cloud computing. We propose a cloud-deployed MPC as a Service (MPCaaS) to help eliminate the barriers to adoption and enable more organizations and individuals to handle their shared data processing securely. The growing presence of Field Programmable Gate Array (FPGA) hardware in datacenters enables accelerated computing as well as low latency, high bandwidth communication that bolsters the performance of MPC. Developing an abstract service that employs this hardware will democratize access to MPC, rather than restricting it to the small overlapping pools of users knowledgeable about both cryptography and hardware accelerators. A hardware proof of concept we have implemented at BU supports this idea. We deployed an efficient three-party Secret Sharing (SS) protocol supporting both Boolean and arithmetic shares on FPGA hardware. We compare our hardware design to the original authors' software implementations of Secret Sharing and to research results accelerating MPC protocols based on Garbled Circuits with FPGAs. Our conclusion is that Secret Sharing in the datacenter is competitive and, when implemented on FPGA hardware, is able to use at least 10×\times fewer computer resources than the original work using CPUs. Finally, we describe the ongoing work and envision research stages that will help us to build a complete MPCaaS system
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