Recent concerns about privacy issues motivated data mining researchers to develop methods for performing data mining while preserving the privacy of individuals. However, the curr...
Albert Levi, Erkay Savas, Mahir Can Doganay, Thoma...
Abstract. This paper introduces an efficient privacy-preserving protocol for distributed K-means clustering over an arbitrary partitioned data, shared among N parties. Clustering i...
Maneesh Upmanyu, Anoop M. Namboodiri, Kannan Srina...
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...
In this paper we introduce a framework for privacypreserving distributed computation that is practical for many real-world applications. The framework is called Peers for Privacy ...
Yitao Duan, NetEase Youdao, John Canny, Justin Z. ...
Sorting is among the most fundamental and well-studied problems within computer science and a core step of many algorithms. In this article, we consider the problem of constructing...