In this paper we explore private computation built on vector addition and its applications in privacypreserving data mining. Vector addition is a surprisingly general tool for imp...
Secure multiparty computation (MPC) allows joint privacy-preserving computations on data of multiple parties. Although MPC has been studied substantially, building solutions that ...
Martin Burkhart, Mario Strasser, Dilip Many, Xenof...
Data mining, with its promise to extract valuable, previously unknown and potentially useful patterns or knowledge from large data sets that contain private information is vulnerab...
In this paper, we propose a post randomization technique to learn a Bayesian network (BN) from distributed heterogeneous data, in a privacy sensitive fashion. In this case, two or ...
Nowadays organizations all over the world are dependent on mining gigantic datasets. These datasets typically contain delicate individual information, which inevitably gets expose...