Speaker: Yupeng Zhang
University of Maryland
Title: "Security and Privacy of Outsourced Data and Computations"
Date: Monday, 5 March 2018
Time: 4:00pm - 5:00pm
Venue: Lecture Theater F (near lift 25/26), HKUST
Nowadays many users outsource their data and computation to cloud-service
providers such as Amazon EC2, Google Cloud, and Microsoft Azure that are
potentially untrusted or may be compromised. Meanwhile, companies are
collecting more and more data from users so as to run machine-learning
algorithms on that data to develop products and services. Despite of the
great benefits of these techniques, they currently require users to give
up control of their data and to trade off privacy for utility.
I will discuss several cryptographic techniques I have developed to
address these issues. I will first talk about techniques for verifiable
storage and computation that can be used to ensure the correctness of
computations done in the cloud and services offered by cloud providers. I
will then discuss privacy-preserving machine learning, which allows
companies to execute machine-learning algorithms without learning users'
data. I will conclude with some thoughts on future applications of these
new protocols to other domains.
Yupeng Zhang is a PhD student at the University of Maryland, working with
Professors Charalampos Papamanthou and Jonathan Katz. His research is
focused on applied cryptography, and his work on verifiable computation,
privacy-preserving machine learning, and searchable encryption has been
published at top security conferences. He is a recipient of Google PhD
Fellowship and receives Outstanding Graduate Assistant Award of the
University of Maryland.