Abstract: Fusion of information from graph features and content can provide superior inference for an anomaly detection task, compared to the corresponding content-only or graph fe...
John Grothendieck, Carey E. Priebe, Allen L. Gorin
Abstract We address the problem of monitoring and identification of correlated burst patterns in multi-stream time series databases. We follow a two-step methodology: first we iden...
This paper proposes WIDS, a wireless intrusion detection system, which applies data mining clustering technique to wireless network data captured through hardware sensors for purp...
Christie I. Ezeife, Maxwell Ejelike, Akshai K. Agg...
The conflict between resource consumption and query performance in the data mining context often has no satisfactory solution. This not only stands in sharp contrast to the need of...
Matthias Gimbel, Michael Klein, Peter C. Lockemann
In this work we propose a novel approach to anomaly detection in streaming communication data. We first build a stochastic model for the system based on temporal communication pa...