In this paper, we study the problem of publishing high-dimensional data in a distributed multi-
party environment under differential privacy. In particular, with the assistance of a semi …

In this paper, we study the novel problem of publishing high-dimensional data in a
distributed multi-party environment under differential privacy. In particular, with the …

In this paper, we study the problem of publishing vertically partitioned data under differential
privacy, where different attributes of the same set of individuals are held by multiple parties …

Releasing high-dimensional data enables a wide spectrum of data mining tasks. Yet,
individual privacy has been a major obstacle to data sharing. In this paper, we consider the …

Privacy-preserving data publishing is an important problem that has been the focus of
extensive study. The state-of-the-art solution for this problem is differential privacy, which …

Differentially private data publication has recently received considerable attention. However,
it faces some challenges in differentially private high-dimensional data publication, such as …

Given a set of local sequential datasets held by multiple parties, we study the problem of
publishing a synthetic dataset that preserves approximate sequentiality information of the …

Internet of Things and the related computing paradigms, such as cloud computing and fog
computing, provide solutions for various applications and services with massive and high …

Releasing raw data sets with sensitive personal information will leak privacy. Therefore,
various differential privacy methods have been proposed for efficient data sharing while …

Various organizations collect data about individuals for various reasons, such as service
improvement. In order to mine the collected data for useful information, data publishing has …