Order-preserving encryption enables performing many classes of queries -including range queries -on encrypted databases. Popa et al. recently presented an ideal-secure order-preserving encryption (or encoding) scheme, but their cost of insertions (encryption) is very high. In this paper we present an also ideal-secure, but significantly more efficient orderpreserving encryption scheme. Our scheme is inspired by Reed's referenced work on the average height of random binary search trees. We show that our scheme improves the average communication complexity from O(n log n) to O(n) under uniform distribution. Our scheme also integrates efficiently with adjustable encryption as used in CryptDB. In our experiments for database inserts we achieve a performance increase of up to 81% in LANs and 95% in WANs.

Secure computation (SC) are cryptographic protocols that enable multiple parties to perform a joint computation while retaining the privacy of their inputs. It is current practice to evaluate the performance of SC protocols using complexity approximations of computation and communication. Due to the disparate complexity measures and constants this approach fails at reliably predicting the performance. We contribute a performance model (PM) for forecasting runtimes of secure two-party computations. We show the correctness of our PM by an empirical study on the problem of secure division which is relevant for many real world SCs, e.g., k-means clustering or supply chain optimization. We show that our PM can be used to make an optimal selection of an algorithm and cryptographic protocol combination, as well as to determine the implicit security tradeoffs. The predictions of our PM can be used to design or select more efficient or more secure protocols.Index Terms-Multi-party Computation Performance Model Security 2011 Eighth International Conference on Quantitative Evaluation of SysTems 978-0-7695-4491-5/11 $26.00

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Benchmarking is the comparison of one company's key performance indicators (KPI) to the statistics of the same KPIs of its peer group. A KPI is a statistical quantity measuring the performance of a business process. Privacy by means of controlling access to data is of the utmost importance in benchmarking. Companies are reluctant to share their business performance data due to the risk of losing a competitive advantage or being embarrassed. We present a cryptographic protocol for securely computing benchmarks between multiple parties and describe the technical aspects of a proof of concept implementation of SAP's research prototype Global Benchmarking Service (GBS) on Microsoft's cloud technology Windows Azure.