![]() Arash Habibi Lashkari, Gerard Draper-Gil, Mohammad Saiful Islam Mamun and Ali A.If you are using our dataset, you should cite our related research paper which outlining the details of the dataset and its underlying principles: The ISCXTor2016 dataset is publicly available for researchers. P2P: uTorrent and Transmission (Bittorrent).VoIP: Facebook, Skype and Hangouts voice calls.File Transfer: Skype, FTP over SSH (SFTP) and FTP over SSL (FTPS) using Filezilla and an external service.Chat: ICQ, AIM, Skype, Facebook and Hangouts.UNB-CIC Tor Network Traffic Dataset content The UNB CIC Network Traffic (Tor-nonTor) dataset consists of labeled network traffic, including full packet in pcap format and csv (flows generated by ISCXFlowMeter) also are publicly available for researchers. ISCXFlowMeter has been written in Java for reading the pcap files and create the csv file based on selected features. Then, we labelled all flows from the Tor. pcap files captured at the workstation: we extracted the flows, and we confirmed that the majority of traffic flows were generated by application X (Skype, ftps, etc.), the object of the traffic capture. Later, we labelled the captured traffic in two steps. pcap files: one regular traffic pcap (workstation) and one Tor traffic pcap (gateway) file. To facilitate the labeling process, as we explained in the related published paper, we captured the outgoing traffic at the workstation and the gateway simultaneously, collecting a set of pairs of. The traffic was captured using Wireshark and tcpdump, generating a total of 22GB of data. ![]() We also used different combinations of upload and download speeds. torrent files from the Kali linux distribution and captured traffic sessions using the Vuze application. To generate this traffic we downloaded different. P2P: This label is used to identify file-sharing protocols like Bittorrent. Within this label we captured voice-calls using Facebook, Hangouts and Skype. ![]() VoIP: The Voice over IP label groups all traffic generated by voice applications. For our dataset we captured Skype file transfers, FTP over SSH (SFTP) and FTP over SSL (FTPS) traffic sessions. We captured traffic from YouTube (HTML5 and flash versions) and Vimeo services using Chrome and Firefox.įTP: This label identifies traffic applications whose main purpose is to send or receive files and documents. Video-Streaming: The streaming label identifies video applications that require a continuous and steady stream of data. Under this label we have Facebook and Hangouts via web browser, Skype, and IAM and ICQ using an application called pidgin.Īudio-Streaming: The streaming label identifies audio applications that require a continuous and steady stream of data. The clients were configured to deliver mail through SMTP/S, and receive it using POP3/SSL in one client and IMAP/SSL in the other.Ĭhat: The chat label identifies instant-messaging applications. For the non-Tor traffic we used previous benign traffic from VPN project and for the Tor traffic we used 7 traffic categories:īrowsing: Under this label we have HTTP and HTTPS traffic generated by users while browsing (Firefox and Chrome).Įmail: Traffic samples generated using a Thunderbird client, and Alice and Bob Gmail accounts. We created three users for the browser traffic collection and two users for the communication parts such as chat, mail, FTP, p2p, etc. To be sure about the quantity and diversity of this dataset in CIC, we defined a set of tasks to generate a representative dataset of real-world traffic.
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