  Benchmarking is an important measure for companies to investigate their
performance and to increase efficiency. As companies usually are reluctant to
provide their key performance indicators (KPIs) for public benchmarks,
privacy-preserving benchmarking systems are required. In this paper, we present
an enhanced privacy-preserving benchmarking protocol that is based on
homomorphic encryption. It enables cloud-based KPI comparison including the
statistical measures mean, variance, median, maximum, best-in-class, bottom
quartile, and top quartile. The theoretical and empirical evaluation of our
benchmarking system underlines its practicability. Even under worst-case
assumptions regarding connection quality and asymmetric encryption
key-security, it fulfils the performance requirements of typical KPI
benchmarking systems.
