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SCVIC-TS-2022: Network intrusion data with original raw network packets
- Citation Author(s):
-
JinxinLiu
University of OttawaMuratSimsekUniversity of OttawaMicheleNogueiraFederal University of Minas GeraisBurakKantarciUniversity of Ottawa - Submitted by:
- Burak Kantarci
- Last updated:
- Sun, 09/03/2023 - 00:25
- DOI:
- 10.21227/qm9h-8c05
- Data Format:
- License:
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- Keywords:
Abstract
SCVIC-TS-2022: Network intrusion data with original raw network packets
To apply Time Series Network Flow Meter (TS-NFM), a network intrusion dataset must have original raw network packets rather than extracted features and complete labeling information; consequently, this dataset uses the CIC-IDS-2017 dataset (I. Sharafaldin, A. Habibi Lashkari, and A. A. Ghorbani, “Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characterization:,” in Proc. of the 4th Intl. Conf. on Information Systems Security and Privacy, 2018). The raw network packets (PCAP format) are fed into the TS-NFM proposed in our paper* with a time window of two minutes (same to the extracted features from CIC-IDS-2017), resulting in the SCVIC-TS-2022 dataset. MTS's maximum length L is 511,681 due to the network's fast speed. The number of features/dimensions d is thirteen, which includes the direction of a packet, IAT, size in bytes, and ten TCP flags.
*If you are using the SCVIC-TS-2022 dataset, please cite the following paper:
J.Liu, M.Simsek, M. Nogueira, B. Kantarci, "Multidomain transformer-based deep learning for early detection of network intrusion," IEEE Global Communications Conference (Globecom), Kuala Lumpur, Malaysia, pp. 1-6, December 2023.
SCVIC-TS-2022: Network intrusion data with original raw network packets
To apply Time Series Network Flow Meter (TS-NFM), a network intrusion dataset must have original raw network packets rather than extracted features and complete labeling information; consequently, this dataset uses the CIC-IDS-2017 dataset (I. Sharafaldin, A. Habibi Lashkari, and A. A. Ghorbani, “Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characterization:,” in Proc. of the 4th Intl. Conf. on Information Systems Security and Privacy, 2018). The raw network packets (PCAP format) are fed into the TS-NFM proposed in our paper* with a time window of two minutes (same to the extracted features from CIC-IDS-2017), resulting in the SCVIC-TS-2022 dataset. MTS's maximum length L is 511,681 due to the network's fast speed. The number of features/dimensions d is thirteen, which includes the direction of a packet, IAT, size in bytes, and ten TCP flags.
*If you are using the SCVIC-TS-2022 dataset, please cite the following paper:
J.Liu, M.Simsek, M. Nogueira, B. Kantarci, "Multidomain transformer-based deep learning for early detection of network intrusion," IEEE Global Communications Conference (Globecom), Kuala Lumpur, Malaysia, pp. 1-6, December 2023.
