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:
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 Webex | Features 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:
Hope you enjoyed this post and the paper itself! For more info you can always contact us by email.
