Preserving Statistical Privacy in Distributed Optimization

Per-se Privacy Preserving Distributed Optimization

Distributed optimization is a fundamental mathematical theory for parallel and distributed systems. Several applications are normally designed based on such a theory, where parties cooperatively exchange messages with little or no central coordination to achieve some goals. In many situations, the transactions among the parties must be private, such as among members of social networks, hospital...

Privacy-preserving Statistical Query and Processing on Distributed OpenEHR Data

UNLABELLED Reuse of data from EHRs is essential for many purposes. The objective of the study was to explore how distributed electronic health record (EHR) data can be reused for privacy-preserving statistical query and processing. METHOD We have designed and created a proof of concept prototype solution based on the OpenEHR specification to ensure interoperability and to query the EHRs. XMPP...

Distributed Privacy-Preserving Methods for Statistical Disclosure Control

Privacy - Preserving Distributed Computation

P4P: A Practical Framework for Privacy-Preserving Distributed Computation

Privacy-preserving distributed clustering

Clustering is a very important tool in data mining and is widely used in on-line services for medical, financial and social environments. The main goal in clustering is to create sets of similar objects in a data set. The data set to be used for clustering can be owned by a single entity, or in some cases, information from different databases is pooled to enrich the data so that the merged data...