MINA

Abstract

Connecting geographically dispersed sites by layer two virtual private networks is a widely deployed, cost effective, and reliable technology. The key feature of layer two virtual private networks is confidentiality. However, L2 VPNs are being rapidly replaced by layer three virtual networks as common carriers expand the roles of their shared IP networks. The recent increase of interest in L3 virtual networks has led to renewed interest and new questions concerning their privacy.We designate virtual network nodes that are undesirable as extrinsic. In this paper we propose a novel algorithm, Message Induced Network Appraisal (MINA), for detecting the presence of extrinsic nodes in virtual networks. MINA is inspired by Kleinberg's HITS algorithm for ranking web pages. The generalization of a HITS derived algorithm to detecting the presence of extrinsic nodes in virtual networks is novel.Our MINA algorithm constructs the communication graph induced by message exchange, scores the participating nodes to identify mutual nodes, and detects the presence of extrinsic nodes. Using the MINA algorithm, network users are presented with a useful indicator about the confidentiality of their L3 virtual network. In this paper we describe MINA and demonstrate that our method reliably detects the presence of extrinsic nodes in L3 virtual networks.