About MAWILab
MAWILab is a database that assists researchers to evaluate their traffic anomaly detection methods. It consists of a set of labels locating traffic anomalies in the MAWI archive (samplepoints B and F). The labels are obtained using an advanced graph-based methodology that compares and combines different and independent anomaly detectors. The data set is daily updated to include new traffic from upcoming applications and anomalies.
We are planning to improve the quality and the variety of the labels over time by including the results from emerging anomaly detectors. Therefore, we encourage researchers to submit us their results or detectors so we can maintain a reliable labeling of the MAWI archive.
News
November 2010: MAWILab will be presented at CoNEXT 2010.
MAWILab results from a graph-based methodology that will be presented the 1st of December at CoNEXT 2010 in Philadelphia.
July 2010: The first version of MAWILab is online.
This version contains labeled anomalies for more than nine years of backbone traffic. For this version the labels are the result of the combination of four diverse detectors based on different theoretical backgrounds: the Principal Component Analysis, the Gamma distribution, the Kullback–Leibler divergence and the Hough transform.