| Raw network data was collected over a period of 5 days, Monday through Friday, and stored in PCAP files. | |
| Monday was used to create most of the Benign data, while the Attack-Network implemented various types of attacks over the next 4 days, | |
| such as Brute Force connections (FTP and SSH), several types of DoS attacks, as well as a Botnet attack, Infiltration attacks and subsequent Port-Scanning activity. | |
| The PCAP data was processed using a tool developed by one of the authors of [1], called CICFlowMeter [3]. | |
| This tool produces flow traces: sequences of packets between specific source and destination IP, with corresponding values for source and destination ports. | |
| TCP flows are usually terminated by connection teardowns, while UDP flows are terminated by a flow timeout. | |
| For each of these flow traces many features were selected, measuring flow characteristics, such as packet size, number of packets, flow duration, etc. | |
| For some of these variables, statistics such as their mean and standard deviations are provided as features as well. | |
| While several features are categorical (such as IP addresses, Port numbers and TCP flag counts), most of the other features are numerical. | |
| The result is the CICIDS-2017 dataset, with about 80 features and several attack families which can ultimately be divided in 16 categories: | |
| one Benign category and 15 Attack categories. This original dataset is available at [4]. Subsequently, the authors of [2] spent a lot of effort | |
| to correct some errors in the dataset, by fixing the CICFlowMeter software (especially regarding TCP flow terminations) and by | |
| re-labeling some of the samples accordingly. They posted the corrected dataset on their website [5]; | |
| this also has links to their GitHub site, which provides Python code that can be used to efficiently import the data. | |
| I used that as a starting point for my notebook, here on Kaggle. | |
| For each of the 5 days a csv file with network flows was produced. | |
| These are the files in the dataset, with some changes: I created decimal values for the IP-addresses, and I removed a couple of rows with inf values. | |
| [1] Sharafaldin I., Lashkari A.H., and Ghorbani A.A. Toward generating a new intrusion detection dataset and intrusion traffic characterization, Proceedings of the 4th International Conference on Information Systems Security and Privacy ICISSP - Volume 1, 108-116, 2018. | |
| [2] Engelen G., Rimmer V., and Joosen W. Troubleshooting an intrusion detection dataset: the CICIDS2017 case study, 2021 IEEE Security and Privacy Workshops (SPW), 2021:7-12. | |
| [3] https://www.unb.ca/cic/research/applications.html | |
| [4] https://www.unb.ca/cic/datasets/ids-2017.html | |
| [5] https://intrusion-detection.distrinet-research.be/CNS2022/index.html | |