datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
CICIoT2023Small
CICIoT2023
This dataset provides a processed derivative of the CICIoT2023 traffic collection. The repository organizes truncated PCAP files and flow-based CSV extractions aligned to the original CICResearch folder hierarchy.
Processing Workflow
The processing pipeline follows four stages:
Source acquisition from the CICResearch CICIoT2023 portal.
Flow extraction from full PCAP files using TriFlowMeter.
PCAP size reduction by truncating packet payloads to 128 bytes with… See the full description on the dataset page: https://huggingface.co/datasets/somnath0100/CICIoT2023Small.CICIOT2023-PARQUET
CICIoT2023 — ipfixprobe flow records (Parquet)
1,479,074,715 bidirectional network flows re-exported from the raw PCAPs of
CICIoT2023 (Canadian
Institute for Cybersecurity, University of New Brunswick) with
ipfixprobe 5.7.0, stored as 308 Parquet
files (~19.4 GB) covering 33 attack classes + benign traffic from the
105-device IoT testbed.
The original dataset ships ~587 GB of PCAPs and CSV features computed with a
closed pipeline. This conversion provides an alternative… See the full description on the dataset page: https://huggingface.co/datasets/Lystea/CICIOT2023-PARQUET.CIC-IoT-2023
CIC-IoT-2023 IoT Intrusion Detection Dataset
The CICIoT2023 dataset from the Canadian Institute for Cybersecurity, subsampled and preprocessed for machine learning evaluation.
Configurations
random_3way (default) — 80/10/10 Three-Way Split
Stratified random split with fully separated train/test/validation sets:
Train (80%): Model training and architecture search
Test (10%): Threshold calibration (held out from training)
Validation (10%): Final reported metrics… See the full description on the dataset page: https://huggingface.co/datasets/lacg030175/CIC-IoT-2023.CIC-IoT-2023-neto-full
CIC-IoT-2023 — Neto-Full (Authoritative 46.7M)
This is the authoritative canonical CIC-IoT-2023 dataset at the row count
published by Neto et al. (2023): 46,686,579 rows × 46 features.
Sourced from the Kaggle mirror akashdogra/ciciot23csv (13.75 GB single CSV)
which itself was derived from CIC's official 169-file distribution. Compared
to bencorn's HF mirror (45M, 39 features), this preserves:
All 46 original features (bencorn dropped 7)
The full 46.7M row count (bencorn re-merge… See the full description on the dataset page: https://huggingface.co/datasets/lacg030175/CIC-IoT-2023-neto-full.CIC-IoT-2023
CIC-IoT-2023 IoT Intrusion Detection Dataset
The CICIoT2023 dataset from the Canadian Institute for Cybersecurity, subsampled and preprocessed for machine learning evaluation.
Configurations
random_3way (default) — 80/10/10 Three-Way Split
Stratified random split with fully separated train/test/validation sets:
Train (80%): Model training and architecture search
Test (10%): Threshold calibration (held out from training)
Validation (10%): Final reported metrics… See the full description on the dataset page: https://huggingface.co/datasets/siyam21/CIC-IoT-2023.CIC-IoT-2023-neto-subsample
CIC-IoT-2023 — Neto-Subsample (1.3M, 46-feature canonical)
Stratified subsample (~1,429,753 rows) of the canonical Neto 46.7M
dataset (lacg030175/CIC-IoT-2023-neto-full). Same 46-feature schema as the
full version. Drop-in replacement for lacg030175/CIC-IoT-2023 (1.3M
bencorn-derived, 39 features) for new experiments needing the canonical
feature set.
Subsample composition:
Benign: 200,000 rows
Each attack subclass: up to 50,000 rows
NaN/Inf preserved (no dropna). Pair with… See the full description on the dataset page: https://huggingface.co/datasets/lacg030175/CIC-IoT-2023-neto-subsample.CIC-IoT-2023-full
CIC-IoT-2023 Full Dataset (46M+ rows)
The FULL CICIoT2023 dataset — all 38,508,041 rows, no subsampling.
Configuration
random_3way (default) — 80/10/10 Three-Way Split
Stratified random split with fully separated sets:
Train (80%): 30,806,432 rows — model training and architecture search
Test (10%): 3,850,804 rows — threshold calibration (held out from training)
Validation (10%): 3,850,805 rows — final reported metrics (never touched)
from datasets import… See the full description on the dataset page: https://huggingface.co/datasets/lacg030175/CIC-IoT-2023-full.CIC-IoT-2023-canonical-neto
CIC-IoT-2023 — Canonical (Neto et al.) Variant
This is the canonical CIC-IoT-2023 dataset, sourced from
bencorn/CIC-IoT-2023's
CSV/MERGED_CSV/ folder, which contains Neto et al.'s authentic merged CSVs
WITH embedded labels (vs. bencorn's other CSV/CSV/<attack>/ re-organization
which lost ~6.5M rows during the folder-restructure).
Why this exists: prior lacg030175/CIC-IoT-2023-full and -full-raw were
built from CSV/CSV/ and contained only 38.5M rows. This one contains
~45,019,243… See the full description on the dataset page: https://huggingface.co/datasets/lacg030175/CIC-IoT-2023-canonical-neto.CICIoTLabeledCIC-IoT-2023
CIC-IoT-2023 IoT Intrusion Detection Dataset
The CICIoT2023 dataset from the Canadian Institute for Cybersecurity, subsampled and preprocessed for machine learning evaluation.
Configurations
random_3way (default) — 80/10/10 Three-Way Split
Stratified random split with fully separated train/test/validation sets:
Train (80%): Model training and architecture search
Test (10%): Threshold calibration (held out from training)
Validation (10%): Final reported metrics… See the full description on the dataset page: https://huggingface.co/datasets/casscloud/CIC-IoT-2023.ciciot2023CIC-IoT-2023-raw
CIC-IoT-2023 (1.3M subsample, raw variant)
Companion to lacg030175/CIC-IoT-2023. This variant preserves rows with NaN or ±infinity values in any feature column (the original dataset drops them via pd.dropna). Intended for use with ThermometerEncoder(invalid_encoding="single_bit"), which treats missing / undefined values as a learnable is_invalid flag bit rather than silently encoding them as zero.
Row counts
Full dataset: 1,342,371 rows, 50 (0.004%) with NaN in numeric… See the full description on the dataset page: https://huggingface.co/datasets/lacg030175/CIC-IoT-2023-raw.CIC-IoT-2023-full
CIC-IoT-2023 Full Dataset (46M+ rows)
The FULL CICIoT2023 dataset — all 38,508,041 rows, no subsampling.
Configuration
random_3way (default) — 80/10/10 Three-Way Split
Stratified random split with fully separated sets:
Train (80%): 30,806,432 rows — model training and architecture search
Test (10%): 3,850,804 rows — threshold calibration (held out from training)
Validation (10%): 3,850,805 rows — final reported metrics (never touched)
from datasets import… See the full description on the dataset page: https://huggingface.co/datasets/binhuang0013/CIC-IoT-2023-full.CICIoT2023TruncatedCIC_IoT2023