AIDA: EFFICIENT ALGORITHM FOR ANONYMOUS SHARING OF PRIVATE DATA IN DISTRIBUTED NETWORKS

Abstract

The network society places great demand on the dissemination and sharing of private data. As privacy concerns grow, anonymity of communications becomes important. This paper addresses the issue of anonymous ID assignment to nodes in a distributed network and how it can be integrated with secure mining algorithms to allow nodes that have privacy concerns, a capability to opt out of the mining computation. In this paper anonymous ID used for hiding the data sharing, also allows multiple partied 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. Technique is utilized iteratively to assign the nodes ID numbers ranging from 1…N,sanctions more complex data to be shared and has applications to other quandaries in collision avoidance in communications and distributed database access.We propose two algorithms for ID assignment and evaluate their performance. We use them in the design of a protocol that allows a node to opt out of data mining, and investigate the collusion resistance capability of the resulting protocol.