README.md

metadata

license: other
license_name: cic-ids-2017-research-use
license_link: https://www.unb.ca/cic/datasets/ids-2017.html
task_categories:
  - tabular-classification
language:
  - en
tags:
  - tsfile
  - time-series
  - network-security
  - cybersecurity
  - netflow
  - flow
  - intrusion-detection
  - nids
  - canonical-schema
  - flowprep
  - deeptempo
pretty_name: CIC-IDS-2017 Canonical NetFlow Flowprep TsFile
size_categories:
  - 100K<n<1M
modality: timeseries
configs:
  - config_name: default
    data_files:
      - split: train
        path: cic_ids_2017_flowprep.tsfile

CIC-IDS-2017 Canonical NetFlow Flowprep (TsFile)

This repository contains an Apache TsFile conversion of DeepTempo/cic-ids-2017-flowprep, a small CIC-IDS-2017 demonstration slice canonicalized by DeepTempo's flowprep tool into a typed NetFlow schema.

Modalities: Time-series.

Source Dataset

• Original dataset: DeepTempo/cic-ids-2017-flowprep
• Source artifact: data/cic-ids-2017-canonical.parquet
• Rows: 101,094 flows
• Columns: 13 source columns
• Task: binary intrusion-detection / tabular classification
• Source format: ZSTD-compressed Parquet, single row group
• Source timestamp encoding: int64 epoch microseconds
• Source license metadata: other, cic-ids-2017-research-use
• License link: https://www.unb.ca/cic/datasets/ids-2017.html

The source dataset is a clean canonical NetFlow table produced by flowprep from a CIC-IDS-2017 sample. It is a demonstration slice, not the full CIC-IDS-2017 dataset. For research use, refer to the official UNB CIC dataset page and cite the original CIC-IDS-2017 paper.

Converted Data

• TsFile path: cic_ids_2017_flowprep.tsfile
• TsFile table: cic_ids_2017_flowprep
• Rows: 101,094
• Converted columns: 14 including Time and generated event_rank
• Device/TAG groups: 1,780
• Time precision: microseconds
• Time range: 2017-03-07 01:00:01 UTC to 2017-07-07 12:59:00 UTC
• Class balance: 81,171 benign / 19,923 attack

TsFile Schema

timestamp is converted to the TsFile Time column as epoch microseconds and is not retained as a duplicate FIELD.

TAG columns:

• attack
• label
• event_rank

FIELD columns:

• src_ip
• dest_ip
• src_port
• dest_port
• fwd_bytes
• bwd_bytes
• fwd_pkts
• bwd_pkts
• flow_dur
• protocol

protocol is null for all rows in this source slice and is preserved as a nullable numeric FIELD for canonical-schema fidelity.

Conversion Notes

This is a network-flow event table. High-cardinality endpoint columns such as src_ip, dest_ip, src_port, and dest_port are kept as FIELD columns rather than TAG/device keys. The low-cardinality ground-truth columns attack and label are TAGs for efficient filtering.

event_rank is a generated TAG that preserves all concurrent flows without modifying Time. It is the duplicate order within (attack, label, Time). In this source snapshot, event_rank ranges from 0 to 1,587 and 88,916 rows have a nonzero rank. The final (attack, label, event_rank, Time) key has no duplicates.

No source rows are dropped. The source timestamp column is represented by TsFile Time; all other source columns are represented either as TAG or FIELD columns.

Minimal Read Example

Read the .tsfile file with the Apache TsFile Java or Python SDK.

Example logical filter:

SELECT *
FROM cic_ids_2017_flowprep
WHERE attack = 'attack'

Citation

If you use the data, cite the original CIC-IDS-2017 paper:

@inproceedings{sharafaldin2018toward,
  title     = {Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characterization},
  author    = {Sharafaldin, Iman and Lashkari, Arash Habibi and Ghorbani, Ali A.},
  booktitle = {Proceedings of the 4th International Conference on Information Systems Security and Privacy (ICISSP)},
  year      = {2018}
}