Secure MPC for analytics as a web application
Files
Accepted manuscript
Date
2016-01-01
Authors
Lapets, Andrei
Volgushev, Nikolaj
Bestavros, Azer
Jansen, Frederick
Varia, Mayank
Version
OA Version
Citation
Andrei Lapets, Nikolaj Volgushev, Azer Bestavros, Frederick Jansen, Mayank Varia. 2016. "Secure MPC for analytics as a web application." 2016 IEEE Cybersecurity development (IEEE SECDEV 2016). IEEE Cybersecurity Development (SecDev). Boston, MA, 2016-11-03 - 2016-11-04
Abstract
Companies, government agencies, and other organizations have been analyzing data pertaining to their internal operations with great effect, such as in evaluating performance or improving efficiency. While each organization's own data is valuable internally, aggregate data from multiple organizations can have value to the organizations themselves, policymakers, and society. Unfortunately, an organization's data is often proprietary and confidential, and its release may be potentially deleterious to the organization's interests. Secure multi-party computation (MPC) resolves this tension: aggregate data may be computed while protecting each contributor's confidentiality. Theoretical constructs have been known for decades [1]-[3] and recent efforts aim to deliver them to end-users [4]-[6].