Visible to the public A Graph-Theoretic Approach to Virtual Access Point Correlation

TitleA Graph-Theoretic Approach to Virtual Access Point Correlation
Publication TypeConference Paper
Year of Publication2017
AuthorsRoth, J. D., Martin, J., Mayberry, T.
Conference Name2017 IEEE Conference on Communications and Network Security (CNS)
ISBN Number978-1-5386-0683-4
Keywords802.11 access point implementation, Communication system security, computer network security, Correlation, functional improvement, graph theory, graph-theoretic approach, IEEE 802.11 Standard, individual provider, insecure network, logically separate networks, nascent wireless functionality management, Network reconnaissance, Network topology, physical equipment, Probes, pubcrawl, Resiliency, secure network, security, security standpoint, standardization process, telecommunication network management, VAP identification algorithm, virtual access point correlation, wireless LAN, wireless networks

The wireless boundaries of networks are becoming increasingly important from a security standpoint as the proliferation of 802.11 WiFi technology increases. Concurrently, the complexity of 802.11 access point implementation is rapidly outpacing the standardization process. The result is that nascent wireless functionality management is left up to the individual provider's implementation, which creates new vulnerabilities in wireless networks. One such functional improvement to 802.11 is the virtual access point (VAP), a method of broadcasting logically separate networks from the same physical equipment. Network reconnaissance benefits from VAP identification, not only because network topology is a primary aim of such reconnaissance, but because the knowledge that a secure network and an insecure network are both being broadcast from the same physical equipment is tactically relevant information. In this work, we present a novel graph-theoretic approach to VAP identification which leverages a body of research concerned with establishing community structure. We apply our approach to both synthetic data and a large corpus of real-world data to demonstrate its efficacy. In most real-world cases, near-perfect blind identification is possible highlighting the effectiveness of our proposed VAP identification algorithm.

Citation Keyroth_graph-theoretic_2017