Henry Corrigan-Gibbs: 2017 Security Workshop


Monday, April 10, 2017
Location: McCaw Hall, Arrillaga Alumni Center

"Prio: Private, Robust, and Scalable Computation of Aggregate Statistics"



This talk will present Prio, a privacy-preserving system for the collection of aggregate statistics. Each Prio client holds a private data value (e.g., its current location), and a small set of servers compute statistical functions over the values of all clients (e.g., the most popular location). As long as at least one server is honest, the Prio servers learn nearly nothing about the clients' private data, except what they can infer from the aggregate statistics that the system computes. To protect functionality in the face of faulty or malicious clients, Prio uses secret-shared non-interactive proofs (SNIPs), a new cryptographic technique that yields a hundred-fold performance improvement over conventional zero-knowledge approaches. Prio extends classic private aggregation techniques to enable the collection of large class of useful statistics. For example, Prio can perform a least-squares regression on high-dimensional client-provided data without ever seeing the data in the clear.

This is joint work with Dan Boneh, and our paper on Prio is to appear at NSDI 2017.


Henry Corrigan-Gibbs is a fourth-year PhD student in computer science at Stanford, advised by Dan Boneh. His work applies cryptographic techniques to bring rigorous privacy properties to large-scale computer systems.