Literature Survey on Secure Multiparty Anonymous Data Sharing

Abstract

Abstract:The popularity of internet as a communication medium whether for personal or business requires anonymous communication in various ways. Businesses also have legitimate reasons to make communication anonymous and avoid the consequences of identity revelation. The problem of sharing privately held data so that the individuals who are the subjects of the data cannot be identified has been researched extensively. Researchers have understood the need of anonymity in various application domains: patient medical records, electronic voting, e-mail, social networking, etc. Another form of anonymity, as used in secure multiparty computation, allows multiple parties on a network to jointly carry out a global computation that depends on data from each party while the data held by each party remains unknown to the other parties. The secure computation function widely used is secure sum that allows parties to compute the sum of their individual inputs without mentioning the inputs to one another. This function helps to characterize the complexities of the secure multiparty computation. Another algorithm for sharing simple integer data on top of secure sum is built. The sharing algorithm will be used at each iteration of this algorithm for anonymous ID assignment (AIDA).