We study network-agnostic secure multiparty computation with perfect security. Traditionally MPC is studied assuming the underlying network is either synchronous or asynchronous. In a network-agnostic setting, the parties are unaware of whether the underlying network is synchronous or asynchronous.

The growing volumes of data collected and its analysis to provide better services create worries about digital privacy. The literature has relied on secure multiparty computation techniques to address privacy concerns and give practical solutions. However, recent research has mostly focused on the small-party honest-majority setting of up to four parties, noting efficiency concerns. In this work, we extend the strategies to support a larger number of participants in honest-majority setting with efficiency at the center stage.