Is our ground-truth for traffic classification reliable?
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The validation of the different proposals in the traffic classification literature is a controversial issue. Usually, these works base their results on a ground-truth built from private datasets and labeled by techniques of unknown reliability. This makes the validation and comparison with other solutions an extremely difficult task. This paper aims to be a first step towards addressing the validation and trustworthiness problem of network traffic classifiers. We perform a comparison between 6 well-known DPI-based techniques, which are frequently used in the literature for ground-truth generation. In order to evaluate these tools we have carefully built a labeled dataset of more than 500 000 flows, which contains traffic from popular applications. Our results present PACE, a commercial tool, as the most reliable solution for ground-truth generation. However, among the open-source tools available, NDPI and especially Libprotoident, also achieve very high precision, while other, more frequently used tools (e.g., L7-filter) are not reliable enough and should not be used for ground-truth generation in their current form.
CitacióCarela, V.; Bujlow, T.; Barlet, P. Is our ground-truth for traffic classification reliable?. A: Passive and Active Measurment Conference. "Passive and Active Measurement: 15th International Conference, PAM 2014: Los Angeles, CA, USA: March 10-11, 2014: proceedings". Los Ángeles, CA: 2014, p. 98-108.
Versió de l'editorhttp://link.springer.com/chapter/10.1007%2F978-3-319-04918-2_10
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