Secure Multiparty Computation

Boston University Salary Survey Work

Principals: Andrei Lapets, Boston University

• BOSTON WOMEN’S WORKFORCE COUNCIL REPORT 2016.

"Working with the staff of the Hariri Institute, including Boston University Software & Application Innovation Lab interns and software engineers, we developed a completely confidential reporting system. The essence of this system is that actual wage data is never revealed outside of the company to which it relates. Rather, disguised averages are computed for each demographic category and aggregated across all companies using a technique known as secure multi-party computation, which means the BWWC receives anonymous, aggregated data. The data collected from employers was limited to a set of zip codes that defined the Greater Boston area for reporting purposes. We also asked for cash bonus information and an indication of the average seniority of the workers to provide additional background." pp. 11-12

• User-Centric Distributed Solutions for Privacy-Preserving Analytics, Azer Bestavros, Andrei Lapets, Mayank Varia, Communications of the ACM, Vol. 60 No. 2, Pages 37-39, 10.1145/3029603

• Secure Multi-Party Computation for Analytics Deployed as a Lightweight Web Application, Andrei Lapets, Nikolaj Volgushev, Azer Bestavros, Frederick Jansen, Mayank Varia, Boston University CS Technical Report, August 2016.

• Web-based Multi-Party Computation with Application to Anonymous Aggregate Compensation Analytics, Andrei Lapets Eric Dunton Kyle Holzinger Frederick Jansen Azer Bestavros, Boston University CS Technical Report, September 2015.

Demo

• https://100talent.org/

See Also

• Wikipedia article