Practical privacy-preserving benchmarking

Abstract

Benchmarking is an important process for companies to stay competitive in today's markets. The basis for benchmarking are statistics of performance measures of a group of companies. The companies need to collaborate in order to compute these statistics. Protocols for privately computing statistics have been proposed in the literature. This paper designs, implements and evaluates a privacy-preserving benchmarking platform which is a central entity that offers a database of benchmark statistics to its customers. This is the first attempt at building a practical privacy-preserving benchmarking system and the first attempt at addressing all necessary trade-offs. The paper starts by designing a protocol that efficiently computes the statistics with constant cost per participant. The protocol uses central communication where customers only communicate with the central platform which facilitates a simple practical orchestration of the protocol. The protocols scale to realistic problem sizes due to the constant communication (and computation) cost per participant of the protocol. © 2008 Springer Science+Business Media, LLC.