This paper describes a protocol detection using statistic information about a flow extended by packet sizes and time characteristics, which consist of packet inter-arrival times. The most common way of network traffic classification is a deep packet inspection (DPI). Our approach deals with the DPI disadvantage in power consumption using aggregated IPFIX data instead of looking into packet content. According to our previous experiments, we have found that applications have their own behavioral pattern, which can be used for the applications detection. With a respect to current state of development, we mainly present the idea, the results which we have achieved so far and of our future work. © 2011 Springer-Verlag.
CITATION STYLE
Piskac, P., & Novotny, J. (2011). Using of time characteristics in data flow for traffic classification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6734 LNCS, pp. 173–176). https://doi.org/10.1007/978-3-642-21484-4_21
Mendeley helps you to discover research relevant for your work.