SCVIC-APT-2021

Name: SCVIC-APT-2021
Creator: Burak Kantarci
License: https://creativecommons.org/licenses/by/4.0/

Citation Author(s):: Jinxin Liu (University of Ottawa)

Yu Shen (University of Ottawa)

Murat Simsek (University of Ottawa)

Burak Kantarci (University of Ottawa)

Hussein T. Mouftah (University of Ottawa)

Mehran Bagheri (Ciena)

Petar Djukic (Ciena)
Submitted by:: Burak Kantarci
Last updated:: Mon, 09/26/2022 - 17:39
DOI:: 10.21227/g2z5-ep97
Data Format:: *.csv
Research Article Link:: A New Realistic Benchmark for Advanced Persistent Threats in Network Traffic

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Keywords:

network security

Advanced Persistent Threat (APT)

Intrusion dataset

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Abstract

The dataset has been developed in Smart Connected Vehicles Innovation Centre (SCVIC) of the University of Ottawa in Kanata North Technology Park.

In order to define a benchmark for Machine Learning (ML)-based Advanced Persistent Threat (APT) detection in the network traffic, we create a dataset named SCVIC-APT-2021, that can realistically represent the contemporary network architecture and APT characteristics. Please cite the following original article where this work was initially presented:

Jinxin Liu, Yu Shen, Murat Simsek, Burak Kantarci, Hussein Mouftah, Mehran Bagheri, Petar Djukic, “A New Realistic Benchmark for Advanced Persistent Threats in Network Traffic”, IEEE Networking Letters, vol. 4, no. 3, pp. 162-166, Sept. 2022, doi: 10.1109/LNET.2022.3185553.