TY - GEN
T1 - Data querying and access control for secure multiparty computation
AU - Von Maltitz, Marcel
AU - Bitzer, Dominik
AU - Carle, Georg
N1 - Publisher Copyright:
© 2019 IFIP.
PY - 2019/5/16
Y1 - 2019/5/16
N2 - 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.
AB - 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.
KW - Access Control
KW - Internet of Things
KW - Intervenability
KW - Secure Multiparty Computation
KW - Transparency
UR - http://www.scopus.com/inward/record.url?scp=85066974840&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85066974840
T3 - 2019 IFIP/IEEE Symposium on Integrated Network and Service Management, IM 2019
SP - 171
EP - 179
BT - 2019 IFIP/IEEE Symposium on Integrated Network and Service Management, IM 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IFIP/IEEE Symposium on Integrated Network and Service Management, IM 2019
Y2 - 8 April 2019 through 12 April 2019
ER -