In many important applications, a collection of mutually distrustful parties must perform private computation over multisets. Each party’s input to the function is his private i...
— In this paper, we consider burst detection within the context of privacy. In our scenario, multiple parties want to detect a burst in aggregated time series data, but none of t...
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...
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 ...