Visible to the public Characterising Network-Connected Devices Using Affiliation Graphs

TitleCharacterising Network-Connected Devices Using Affiliation Graphs
Publication TypeConference Paper
Year of Publication2020
AuthorsMillar, K., Cheng, A., Chew, H. G., Lim, C.
Conference NameNOMS 2020 - 2020 IEEE/IFIP Network Operations and Management Symposium
Date PublishedApril 2020
PublisherIEEE
ISBN Number978-1-7281-4973-8
Keywordsaffiliation graphs, computer network management, device discovery and management, encryption-invariant device management strategy, future traffic demand, graph theory, Internet, IP networks, Local area networks, management complexity, network administrators, Network reconnaissance, network-connected devices, passive network reconnaissance, pubcrawl, resilience, Resiliency, Scalability, security analysts, security risk, university campus network
Abstract

Device management in large networks is of growing importance to network administrators and security analysts alike. The composition of devices on a network can help forecast future traffic demand as well as identify devices that may pose a security risk. However, the sheer number and diversity of devices that comprise most modern networks have vastly increased the management complexity. Motivated by a need for an encryption-invariant device management strategy, we use affiliation graphs to develop a methodology that reveals key insights into the devices acting on a network using only the source and destination IP addresses. Through an empirical analysis of the devices on a university campus network, we provide an example methodology to infer a device's characteristics (e.g., operating system) through the services it communicates with via the Internet.

URLhttps://ieeexplore.ieee.org/document/9110309/
DOI10.1109/NOMS47738.2020.9110309
Citation Keymillar_characterising_2020