The search for unknown frequent pattern is one of the core activities in many time series data mining processes. In this paper we present an extension of the pattern discovery pro...
We present techniques for privacy-preserving computation of multidimensional aggregates on data partitioned across multiple clients. Data from different clients is perturbed (rand...
Rakesh Agrawal, Ramakrishnan Srikant, Dilys Thomas
Serious concerns on privacy protection in social networks have been raised in recent years; however, research in this area is still in its infancy. The problem is challenging due ...
Abstract. In this paper, we present a protocol for computing the principal eigenvector of a collection of data matrices belonging to multiple semi-honest parties with privacy const...
We address the problem of preserving privacy in streams, which has received surprisingly limited attention. For static data, a well-studied and widely used approach is based on ra...