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. In this paper, we address the problem of protecting the underlying attribute values when sharing data for clustering. The challenge is how to meet privacy requirements an...
Data mining techniques, in spite of their benefit in a wide range of applications have also raised threat to privacy and data security. This paper addresses the problem of preservi...
S. Srinivasa Rao 0002, K. V. S. V. N. Raju, P. Kus...
Preservation of privacy in micro-data release is a challenging task in data mining. The k-anonymity method has attracted much attention of researchers. Quasiidentifier is a key co...
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...