Amount Awarded: $19,000
Currently we live in the age of so-called Big Data where everything that we do leaves a digital footprint. Unprecedented levels of data are being captured and stored. Sensitive personal information, such as health records, financial information, etc, is stored in corporate data-centers. Furthermore, sophisticated algorithms are being used to analyze this data for numerous applications. For example, data analytic is being used to decode the human genome, accurately predict human behavior, offer personalized medical treatment, and so on. Such applications are extremely useful. However, privacy concerns about what can be learned from such copious amounts of collected data are often raised. The main goal of this project is to envision a world in which Big Data applications can be realized while preserving a high level of privacy. Realizing this world-view will involve solving a number of problems in multiple domains. This project will focus on crucial cryptographic techniques in achieving this vision. In particular, we will develop a toolbox of techniques that allow us to (1) compute on encrypted data and (2) have fine-grained access control to data. Our solutions will be scalable in Big Data settings involving a massive amount of data.