Abstract: 

Oblivious computation refers to the ability to compute on "encrypted" data, such that neither intermediate results nor the program's runtime behavior reveal anything about secret inputs. Oblivious computation can enable privacy-preserving data mining for sensitive data (e.g., genomic or financial data), and allow businesses and individuals to monetize their data without compromising their privacy.

In this talk, I will present a novel, binary-tree based paradigm for constructing Oblivious RAM (ORAM) schemes. ORAM is a generic and powerful primitive that is central to realizing oblivious computation based on either trusted hardware or cryptographic secure computation. Our new ORAM constructions not only solve a thirty-year open theoretical challenge, but also allow ORAM to evolve from a theoretical primitive to a practical building block. Specifically, we made it possible, for the first time, to implement ORAM atop secure processors as well as secure multi-party computation.

Additionally, I will present programming language techniques that not only accelerate oblivious computation, but also make it accessible to real-life programmers who are not security experts. Based on these algorithmic and programming language advances, we have built new platforms for oblivious computation and developed various demo applications such as common data structures, data mining, graph algorithms, and streaming algorithms. Evaluation results suggest that our work has led to four to five orders of magnitude performance improvement for moderately large data sizes, and has enabled a dramatic reduction in application development effort. 

Bio: 

Elaine Shi is an Associate Professor in Cornell University. Her research interests include security, cryptography, distributed systems, foundations of blockchains, and language-based security. She is a recipient of the Packard Fellowship, the Sloan Fellowship, the ONR YIP award, the NSF CAREER award, the NSA Best Scientific Security paper, and various other best-paper and research awards. Elaine obtained her Ph.D. from Carnegie Mellon University. Before joining Cornell, she was an Assistant Professor in UMD.