STPPA Event #2:

Structure: Three talks and one panel related to privacy-enhancing cryptography.

Featured topics: searchable encryption, private set intersection, secure multi-party computation.

Date and place: Monday, April 19, 2021. Virtual event, via Webex

Schedule (Eastern Time):

• 13:00–13:10: Intro: STPPA and PEC.
• 13:10–13:50: An Overview of Encrypted Databases. Seny Kamara (Brown University)
• 13:50–14:30: A Brief Overview of Private Set Intersection. Mike Rosulek (Oregon State University).
• 14:40–15:20: Secure computation on datasets. Steve Lu (Stealth Software Technologies) and Rafail Ostrovsky (UCLA).
• 15:20–16:00: Panel: PEC for privacy and public auditability. Panelist: All speakers; Moderator: the PEC team.

About STPPA: In the "Special Topics on Privacy and Public Auditability" series, the NIST privacy-enhancing cryptography (PEC) project hosts talks on various interconnected topics related to privacy and public auditability. The goal is to convey basic technical background, incite curiosity, suggest research questions and discuss applications, with an emphasis on the role of cryptographic tools.

Talks

Talk 1: An Overview of Encrypted Databases

Speaker: Seny Kamara (Brown University)

Abstract: End-to-end encrypted databases store and process data without ever being able to decrypt it. The widespread availability of practical encrypted databases would greatly improve the security and privacy of our data and would enable a wide array of other privacy-enhancing technologies. In this talk, I will describe the state-of-the-art in encrypted databases in both industry and research.

Bio: Seny Kamara is an associate professor of computer science at Brown University. His research is in cryptography and is driven by real-world problems from privacy, security and surveillance. He has worked extensively on the design and cryptanalysis of encrypted search algorithms, which are efficient algorithms to search on end-to-end encrypted data.

Talk 2: A Brief Overview of Private Set Intersection

Speaker: Mike Rosulek (Oregon State University)

Abstract: Private set intersection (PSI) is a special case of multiparty computation, in which each party has a set of items and the goal is to learn the intersection of those sets while revealing nothing else about those sets. In this talk I will survey and summarize the state of the art for PSI protocol techniques. I will highlight several different categories of PSI techniques, each motivated through different, realistic application scenarios.

Bio: Mike Rosulek is an associate professor in the School of EECS at Oregon State University. His primary research focus is cryptography, specifically protocols for secure computation.

Talk 3: Secure Computation on Datasets

Speakers: Steve Lu (Stealth Software Technologies, Inc.) and Rafail Ostrovsky (UCLA)

Abstract: There are myriad domains where communities could benefit from aggregate statistical analyses that link across databases without requiring data owners to share their underlying data. In many cases, however, an obligation to protect the privacy of the underlying data often prevents organizations from performing (joint) statistical analyses that would benefit the community as a whole. Some common examples include: linking Electronic Medical Records (EMR) for longitudinal studies; student and teacher performance records; monitoring international financial transactions; environmental and hazard records; transportation and automotive studies; studies on logistics for managing vendor and supply chains; personal genetics and ancestry studies; cell phone call and location records; energy efficient HVAC and building management systems; digital statistics and cyber forensics.

In principle, general-purpose secure multiparty computation protocols exist that allow a group of mutually untrusting data owners to compute any function of interest across their joint data. This flexibility of functionality comes at a price, however, and existing MPC compilers target developers with a high-level of cryptographic expertise.  Our work focuses on building a simple, easy-to-deploy interface that allows non-crypto experts to securely compute a limited but optimized set of statistics on jointly held data.

Bios: 

Dr. Steve Lu is the CEO of Stealth Software Technologies, Inc.  Dr. Lu has served as the Principal Investigator on several projects involving secure computation and taking theory to practice. He received his PhD in Mathematics from UCLA under Rafail Ostrovsky in 2009. Within Stealth, Dr. Lu continues to lead ongoing research, design, and implementation of cryptographic tools and libraries. His theoretical contributions include foundational work in Garbled RAM and Distributed Oblivious RAM, and has published over a dozen papers in leading crypto and security venues.

Dr. Rafail Ostrovsky is a Distinguished Professor of Computer Science and Distinguished Professor of Mathematics at UCLA; Fellow of IEEE; Fellow of IACR; and a foreign member of Academia Europaea, with over 300 refereed publications and 14 issued USPTO patents. He served as chair of the IEEE Technical Committee on Mathematical Foundations of Computing from 2015 to 2018 and served as a Chair of FOCS 2011 Program Committee (PC). He also served on over 40 other international conference PC's and is currently serving as associate editor of Journal of ACM, Algorithmica Journal, and Journal of Cryptology. He is the recipient of multiple awards and honors including 1993 Henry Taub Prize; the 2017 IEEE Computer Society Technical Achievement Award and the 2018 RSA Excellence in the Field of Mathematics Award.