We present a framework for mining association rules from transactions consisting of categorical items where the data has been randomized to preserve privacy of individual transact...
Alexandre V. Evfimievski, Ramakrishnan Srikant, Ra...
Reluctance of data owners to share their possibly confidential or proprietary data with others who own related databases is a serious impediment to conducting a mutually beneficia...
Ashish P. Sanil, Alan F. Karr, Xiaodong Lin, Jerom...
Currently, many privacy-preserving data mining (PPDM) algorithms assume the semi-honest model and/or malicious model of multi-party interaction. However, both models are far from ...
Abstract. In this paper, we focus on the problem of preserving the privacy of sensitive relationships in graph data. We refer to the problem of inferring sensitive relationships fr...
In this paper, we investigate privacy-preserving data imputation on distributed databases. We present a privacypreserving protocol for filling in missing values using a lazy deci...