%0 Conference Proceedings
%T Using of Time Characteristics in Data Flow for Traffic Classification
%+ Masaryk University [Brno] (MUNI)
%A Piskac, Pavel
%A Novotny, Jiri
%Z Part 6: PhD Workshop: Monitoring and Security
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 5th Autonomous Infrastructure, Management and Security (AIMS)
%C Nancy, France
%Y Isabelle Chrisment
%Y Alva Couch
%Y Rémi Badonnel
%Y Martin Waldburger
%I Springer
%3 Managing the Dynamics of Networks and Services
%V LNCS-6734
%P 173-176
%8 2011-06-13
%D 2011
%R 10.1007/978-3-642-21484-4_21
%K protocol detection
%K time characteristics
%K flow
%K IPFIX
%K pattern
%Z Computer Science [cs]
%Z Computer Science [cs]/Networking and Internet Architecture [cs.NI]Conference papers
%X 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.
%G English
%Z TC 6
%2 https://inria.hal.science/hal-01585856/document
%2 https://inria.hal.science/hal-01585856/file/978-3-642-21484-4_21_Chapter.pdf
%L hal-01585856
%U https://inria.hal.science/hal-01585856
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC6
%~ IFIP-AIMS
%~ IFIP-LNCS-6734