Information-theoretic metrics hold great promise for modeling traffic and detecting anomalies if only they could be computed
in an efficient, scalable way. Recent advances in streaming estimation algorithms give hope that such computations can be
made practical. We describe our work in progress that aims to use streaming algorithms on 802.11a/b/g link layer (and above)
features and feature pairs to detect anomalies.
This research program is a part of the Institute for Security Technology Studies, supported by Intel Corporation, NSF grant
CCF-0448277, and by Award number NBCH2050002 from the U.S. Department of Homeland Security, Science and Technology Directorate.
Points of view in this document are those of the authors and do not necessarily represent the official position of the U.S.
Department of Homeland Security, Intel Corporation, or any other sponsor.