Design of a Mix Network Using Connectivity Index -- A Novel Privacy Enhancement Approach

Abstract

Privacy Enhancing Techniques (PET) are key to the success in building the trust among the users of the digital world. Enhancing the communication privacy is getting attention nowadays. In this direction, anonymity schemes such as mix, mix networks, onion routing, crowds etc., have started in roads into the deployment at individual and community network levels. To measure the effectiveness and accuracy of such schemes, degree of anonymity is proposed as a privacy metric in literature. To measure the degree of anonymity, many empirical techniques are proposed. We observe that these techniques are computationally intensive and are infeasible for real-time requirements and thus may not be suitable to measure the degree of anonymity under the dynamic changes in the configuration of the network in real-time. In this direction, we propose a novel lightweight privacy metric to measure the degree of anonymity for mix, mix networks and their variants using graph theoretic approach based on Connectivity Index (CI). Further, we also extend this approach with Weighted Connectivity Index (WCI) and have demonstrated the usefulness of the metric through analytical analysis.