Targeted Attack through Network Fingerprinting

Keywords: network fingerprinting, traceroute, ping, MPLS, attacks, connectivity

Abstract

Nowadays, simple tools such as traceroute can be used by attackers to acquire topology knowledge remotely. Worse still, attackers can use a lightweight fingerprinting technique, based on traceroute and ping, to retrieve the routers brand, and use that knowledge to launch targeted attacks.

In this paper, we show that the hardware ecosystem of network operators can greatly vary from one to another, with all potential security implications it brings. Indeed, depending on the autonomous system (AS), not all brands play the same role in terms of network connectivity and network usage (MPLS vs. standard traffic). An attacker could find an interest in targeting a specific hardware vendor in a particular AS, if known defects are present in this hardware, and if the AS relies heavily on it for forwarding its traffic.

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Author Biographies

Emeline Marechal, Montefiore Institue, Belgium

Emeline Marechal received her MS degree in Computer Engineering from the Université de Liège (Belgium) in 2019. She is currently a Ph.D. student at the Montefiore Institute at the Université de Liège. Her research interests are in network measurements, including traffic and topology measurements, and measurement applied to security.

Benoit Donnet, Montefiore Institue, Belgium

Benoit Donnet received his Ph.D. degree in Computer Science from the Université Pierre et Marie Curie in 2006 and has been a PostDoc until 2011 at the Université catholique de Louvain (Belgium). Mr. Donnet joined the Montefiore Institute at the Université de Liège in 2011 where he was appointed successively as Assistant Professor and Associate Professor. His research interests are about Internet measurements (measurements scalability, Internet topology discovery, measurements applied to security), network modeling, middleboxes, new Internet architectures (LISP, Segment Routing), and Computer Science Education.

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Published
2021-04-07
Section
WTMC 2020 Workshop