Privacy-Preserving Routing for Wireless Network using OPERA

Abstract

In wireless network, a routing protocol named privacy-preserving is used which is used to cover-up the actual communication-pair by utilizing the additional traffic. The introduction of dummy traffic is done heuristically that it cannot assure to the latency, transmission cost, etc., in the network topology are optimized. Here, the task is to develop a novel based approach called Optimal Privacy-Preserving Enhancing Routing Algorithm (OPERA) for privacy-preserving and examines the privacy utility problem for wireless networks. In order to implement privacy, we use the statistical decision-making framework called as OPERA. We will use the Bayesian Maximum-a-Posteriori (MAP) which considers the both loosy and looseless observations. We will be solving the privacy-utility tradeoff problem, that can be efficiently solved as a linear program. The simulation that uses OPERA algorithm reduces the probability of adversary detection for up to 5 times compared to baseline schema. OPERA can also perform the theoretic, conventional information and mutual information approach.