SCVIC-CIDS-2021: Collaborative Feature Maps of Networks and Hosts for Intrusion Detection

Citation Author(s):
Jinxin
Liu
University of Ottawa
Murat
Simsek
University of Ottawa
Burak
Kantarci
University of Ottawa
Mehran
Bagheri
Ciena
Petar
Djukic
Ciena
Submitted by:
Burak Kantarci
Last updated:
DOI:
10.21227/ykz8-sy55
Data Format:
Link to Paper:
License:
0
0 ratings - Please login to submit your rating.

Abstract 

SCVIC-CIDS-2021 is a novel dataset that combines network- and host-based data.

 

SCVIC-CIDS-2021 is derived from the meta-data (i.e., network packets, system logs and labeling information) from the well-known benchmark dataset, CIC-IDS-2018 (Iman Sharafaldin, Arash Habibi Lashkari, and Ali A. Ghorbani, “Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characterization”, 4th International Conference on Information Systems Security and Privacy (ICISSP), Portugal, January 2018 ) .

 

In our paper ( J. Liu, M. Simsek, B. Kantarci, M. Bagheri, P. Djukic “Collaborative Feature Maps of Networks and Hosts for AI-driven Intrusion Detection,” IEEE Global Communications Conference (Globecom), Rio de Janeiro, Brazil, December 2022), the generation procedure is described in detail.

Instructions: 

Please see the attachment for details and proper citation of the dataset.

Please use the following citation if you use the dataset for academic research:

@inproceedings{liu2022collaborative,

   title={Collaborative Feature Maps of Networks and Hosts for AI-driven Intrusion Detection},

   author={Liu, Jinxin and Simsek, Murat and Kantarci, Burak and Bagheri, Mehran and Djukic, Petar},

   booktitle={IEEE Global Communications Conference (Globecom)},

   year={2022}

}

Funding Agency: 
Ontario Center for Innovation (OCI)
Grant Number: 
5G ENCQOR 31993