SCVIC-APT-2021

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:
DOI:
10.21227/g2z5-ep97
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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.

The original article where this work was initially presented is as follows:

 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, 2022, doi: 10.1109/LNET.2022.3185553

Instructions: 

Please see the descriptions and instructions in the attached pdf file.

Funding Agency: 
Ontario Center for Innovation (OCI)