On collection of large-scale multi-purpose datasets on internet backbone links
Farnaz Moradi, Magnus Almgren, Wolfgang John, Tomas Olovsson, Philippas Tsigas · 2011
We have collected several large-scale datasets in a number of passive measurement projects on an Internet backbone link belonging to a national university network. The datasets have been used in different studies such as in general classi-fication and characterization of properties of Internet traffic, in network security projects detecting and classifying mali-cious traffic and hosts, and in studies of network-level prop-erties of unsolicited e-mail (spam) traffic. The Antispam dataset alone contains traffic between more than 10 million e-mail addresses. In this paper we describe our datasets, the data collection methodology including experiences in collecting and process-ing data on a large scale. We have in particular selected a dataset belonging to an anti-spam project to show how a practical analysis of highly privacy-sensitive data can be done, in this case containing complete e-mail traffic. Not only do we show that it is possible to collect large datasets, we also show how to solve different issues regarding user privacy and give experiences from how to work with large datasets.