ReliancePoint: A Foundation for Scalable & Secure Computation over Privacy-Sensitive Shared Data

Michael Steiner (Intel Labs)

Big data is created and accumulated each day in many organizations. Mining and analyzing the big data, especially aggregated data across organizations, has the huge benefit of both business and research values. However, loss of privacy or secret information would be detrimental an inhibit widespread applications of data analytics on joint multi-party datasets. As a result, data are locked in data silos, unavailable for research and business analysis.

In this talk, I will present the Reliance Point (RP) technology that supports hosting big data analytics in an untrusted cloud. RP addresses the problem by providing a secure and scalable “neutral environment” for computation based on hardware-based Trusted Execution Environments (TEE). RP enables analytic workflows (pipeline of analytics jobs) by dynamically forming trusted cluster of TEEs, protect data confidentiality and execution integrity while leaving data providers in full control over their data throughout workflow execution.

About Michael Steiner
Dr. Michael Steiner is a Research Scientist at Intel Labs in Hillsboro, OR, USA.  At Intel Labs and in previous positions at IBM Research in India, USA and Switzerland, his work ranged from cryptographic protocol design & analyis, over security architectures & implementations to penetration testing in domains as varied as electronic commerce & payment systems, compliance management, web2.0, cloud and smart grid. Most recently, he is focusing on using hardware-security as foundation to enable scalable multi-party computation.

About Intel Labs
Intel Labs is the research arm of Intel. It fuels Intel’s growth and technology leadership by providing leading edge technologies– not only for current roadmaps, two to five years from now, but also disruptive technology for the “next big thing”! More information here.