Abstract--This paper presents a framework for privacypreserving Gaussian Mixture Model computations. Specifically, we consider a scenario where a central service wants to learn the...
Recently, privacy issues have become important in data analysis, especially when data is horizontally partitioned over several parties. In data mining, the data is typically repre...
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...
—Collaborative spectrum sensing has been regarded as a promising approach to enable secondary users to detect primary users by exploiting spatial diversity. In this paper, we con...
Despite its benefit in a wide range of applications, data mining techniques also have raised a number of ethical issues. Some such issues include those of privacy, data security,...