6.876J (MIT) and CS294-175 (Berkeley)
Advanced Topics in Cryptography Spring 2020
|| Shafi Goldwasser |
|| Calvin Hall 116 (at Berkeley) and 9-151 (at MIT)
||F 10am - 12
Each course participant will deliver one or more lectures on recent research results in cryptography, in consultation with the lecturers.
Each student gives one or more lectures or scribes one or more lectures.
Schedule (subject to change)
Learning vs Verifying
This talk will address the following question: In what cases does learning a good hypothesis require more resources than verifying a hypothesis proposed by someone else?** If verification is significantly cheaper than learning, that could have important practical implications for delegation of machine learning tasks in commercial settings, and might also have consequences for verification of scientific publications, and for AI safety. Two results will be discussed: (1) There exists a learning problem where verification requires quadratically less random samples than are required for learning. (2) The broad class of Fourier-sparse functions (which includes decision trees, for example) can be efficiently verified using random samples only, even though it is widely believed to be impossible to efficiently learn this class from random samples alone.
Jonathan is a PhD student at UC Berkeley. This is joint work with Shafi Goldwasser (UC Berkeley), Guy Rothblum (WIS), and Amir Yehudayoff (Technion).
Publicly Verifiable Non-Interactive Delegation
We construct a delegation scheme for all polynomial time computations. Our scheme is
publicly verifiable and completely non-interactive in the common reference string (CRS) model.
Our scheme is based on an efficiently falsifiable decisional assumption on groups with bilinear maps. Prior to this work, publicly verifiable non-interactive delegation schemes were only
known under knowledge assumptions (or in the Random Oracle model) or under non-standard
assumptions related to obfuscation or multilinear maps.
We obtain our result in two steps. First, we construct a scheme with a long CRS (polynomial
in the running time of the computation) by following the blueprint of Paneth and Rothblum
(TCC 2017). Then we bootstrap this scheme to obtain a short CRS. Our bootstrapping theorem
exploits the fact that our scheme can securely delegate certain non-deterministic computations.
Lisa is a PhD student at MIT. This is joint work with Yael Kalai (Microsoft Research and MIT) and Omer Paneth (Tel-Aviv University).