Towards Practical Privacy Preserving Technology Adoption Analysis Service Platform

Technology adoption analysis is one of the key exercises in managing technology innovation and diffusion. In this paper, we present a service platform for technology adoption analysis, with aim tailored to provide service provisioning to potential technology users and providers. With two service models provided in this platform, a practical privacy preserving framework is developed to help relieve privacy concerns of the platform participants. To illustrate the feasibility of the privacy preserving framework of this platform, an adoption process for RFID technology adoption analysis in logistics and supply chain management is presented to identify key sensitive attributes for background knowledge leading to unique identification of an individual or company.published_or_final_versio

Reuse It Or Lose It: More Efficient Secure Computation Through Reuse of Encrypted Values

Two-party secure function evaluation (SFE) has become significantly more feasible, even on resource-constrained devices, because of advances in server-aided computation systems. However, there are still bottlenecks, particularly in the input validation stage of a computation. Moreover, SFE research has not yet devoted sufficient attention to the important problem of retaining state after a computation has been performed so that expensive processing does not have to be repeated if a similar computation is done again. This paper presents PartialGC, an SFE system that allows the reuse of encrypted values generated during a garbled-circuit computation. We show that using PartialGC can reduce computation time by as much as 96% and bandwidth by as much as 98% in comparison with previous outsourcing schemes for secure computation. We demonstrate the feasibility of our approach with two sets of experiments, one in which the garbled circuit is evaluated on a mobile device and one in which it is evaluated on a server. We also use PartialGC to build a privacy-preserving "friend finder" application for Android. The reuse of previous inputs to allow stateful evaluation represents a new way of looking at SFE and further reduces computational barriers.Comment: 20 pages, shorter conference version published in Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, Pages 582-596, ACM New York, NY, US

Secure Function Evaluation with Ordered Binary Decision Diagrams

Privacy-preserving protocols allow multiple parties with private inputs to perform joint computation while preserving the privacy of their respective inputs. An important cryptographic primitive for designing privacy-preserving protocols is secure function evaluation (SFE). The classic solution for SFE by Yao uses a gate representation of the function that the two parties want to jointly compute. Fairplay is a system that implements the classic solution for SFE. In this paper, we present a new protocol for SFE that uses a graph-based representation of the function. Specifically we use the graph-based representation called ordered binary decision diagrams (OBDDs). For a large number of Boolean functions, OBDDs are more succinct than the gate-based representation. Preliminary experimental results based on a prototype implementation shows that for several functions, our protocol results in a smaller bandwidth than Fairplay. For example, for the classic millionaire’s problem, our new protocol results in a approximately 45 % bandwidth reduction over Fairplay. Therefore, our protocols will be particularly useful for applications for environments with limited bandwidth, such as applications for wireless and sensor networks