Real-Time Classification of Real-Time Communications

This webpage contains additional material of the paper:

Real-Time Classification of Real-Time Communications

(currently under revision)

Year: 2021

Authors: Gianluca Perna, Dena Markudova, Martino Trevisan, Michela Meo, Paolo Garza, Maurizio Munafò, Giovanna Carofiglio

The data

You can find the dataset and the classifiers on this link:

Data and classifiers

The link contains:

  • webex_dataset.csv – a csv file of all 96 features described in the paper, the timestamps, label and video quality calculated for all Webex traffic
  • webex_classifier_trained.pkl – a pickle file of the trained classifier for Webex
  • jitsi_dataset.csv – a csv file of all 96 features described in the paper, the timestamps, label and video quality calculated for all Jitsi traffic
  • jitsi_classifier_trained.pkl – a pickle file of the trained classifier for Jitsi

Note that the classifiers are trained on a subset of their respective dataset (a training set) using only 8 features for Webex and 4 features for Jitsi, as explained in the paper. The time aggregation in the provided csv files is 1s.

Features used for WebexFeatures used for Jitsi
interarrival_len_unique_percent
len_udp_p25
len_udp_p70
len_udp_p75
len_udp_len_unique_percent
rtp_interarrival_p30
rtp_interarrival_len_unique_percent
rtp_marker_sum_check
len_udp_mean
len_udp_p25
len_udp_len_unique_percent
rtp_interarrival_len_unique_percent

The code

The tool used to calculate the features from raw pcap files and log files, by the name of Retina, is available on Github:

Retina


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