SBIR Phase I: Encrypted Databases: From Theory to Systems

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The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project consists of (1) preventing server-level data breaches; and (2) increasing adoption of cloud computing; especially in sectors that inherently deal with sensitive data and are subject to regulation. This includes the healthcare and finance industries as well as government agencies. Data breaches are occurring at an alarming rate and affecting every industry and sector of government. This project enables customers to search and query data without ever needing to decrypt it, effectively protecting data against server-level breaches. Potential customers from the financial and healthcare industries said in interviews that their adoption of cloud computing had been slowed due to the sensitivity of some of their data. Their inability to use the cloud to store and analyze highly sensitive data is very costly since they have to build and maintain on-premise infrastructures to handle it. The outcome of this project will enable customers to make use of and benefit from cloud computing even for their most sensitive data. From a societal standpoint, this project increases user security and privacy and helps achieve regulatory compliance while investing less in cybersecurity.This Small Business Innovation Research (SBIR) Phase I project aims to design, build and evaluate a commercially viable encrypted relational database system. The project will tackle a variety of technical challenges that need to be overcome before this technology can see widespread adoption. The first is integration with existing database management systems (DBMSs). Commercial database systems benefit from over 40 years of research, optimization and engineering breakthroughs. While the new cryptographic techniques proposed for this project have many advantages in terms of security and efficiency, it is not a-priori clear how to integrate them into a standard DBMS without a complete re-design. To address this challenge, this project leverages a new algorithmic paradigm called emulation that seamlessly integrates these new cryptographic techniques with standard commercial DBMSs. The second challenge this project addresses is concrete real-world efficiency. The theoretical analysis of the proposed solution shows that it is asymptotically efficient. The proposed work, however, will show that it is also efficient in practice on real data and against real database benchmarks.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.