Emergent Mind

Data Querying and Access Control for Secure Multiparty Computation

(1901.02651)
Published Jan 9, 2019 in cs.CR and cs.NI

Abstract

In the Internet of Things and smart environments data, collected from distributed sensors, is typically stored and processed by a central middleware. This allows applications to query the data they need for providing further services. However, centralization of data causes several privacy threats: The middleware becomes a third party which has to be trusted, linkage and correlation of data from different context becomes possible and data subject lose control over their data. Hence, other approaches than centralized processing should be considered. Here, Secure Multiparty Computation is a promising candidate for secure and privacy-preserving computation happening close to the sources of the data. In order to make SMC fit for application in these contexts, we extend SMC to act as a service: We provide elements which allow third parties to query computed data from a group of peers performing SMC. Furthermore, we establish fine-granular access control on the level of individual data queries, yielding data protection of the computed results. By adding measures to inform data sources about requests and the usage of their data, we show how a fully privacy-preserving service can be built on the foundation of SMC.

We're not able to analyze this paper right now due to high demand.

Please check back later (sorry!).

Generate a summary of this paper on our Pro plan:

We ran into a problem analyzing this paper.

Newsletter

Get summaries of trending comp sci papers delivered straight to your inbox:

Unsubscribe anytime.