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lacg030175/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.

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Dataset Card

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 ThermometerEncoder(invalid_encoding="single_bit").

Splits

—random_3way: 80% train / 10% test / 10% validation (stratified on binary label, seed=42)
—random: 80% train / 20% test (test = test ∪ validation from random_3way)

Provenance

—Subsampled from lacg030175/CIC-IoT-2023-neto-full (46.7M canonical)
—Originally from akashdogra/ciciot23csv on Kaggle, derived from CIC's official 169-file distribution (Neto et al., 2023).

Class distribution

—DDoS: 552,216 (38.62%)
—DoS: 200,000 (13.99%)
—Benign: 200,000 (13.99%)
—Recon: 189,644 (13.26%)
—Mirai: 150,000 (10.49%)
—Spoofing: 100,000 (6.99%)
—Web-based: 24,829 (1.74%)
—BruteForce: 13,064 (0.91%)